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Recognise your star achievers with this attractive and inexpensive Glass Star Award with silver lined, mirror effect edges to the star.
This award is available in 3 sizes, from 6.25 inches to 7.75 inches high and can be personalised with your own engraved message on the 'Award Body' engraving Area.
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This beautiful glass award is supplied in a black presentation box and will be with you within 3-5 working days from order!
Maximum Engraving Area Sizes for NTC0116.25 inch Award - W:40mm x H:40mm 7 inch Award - W:45mm x H:45mm 7.75 inch Award - W:50mm x H:45mm
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The mentally disturbed killer in the movie: The Silence of the Lambs. He hated his self image so he skinned women and used them as a robe.
by Mister Happyface March 26, 2005
One of the NFL's loveable losers, they were founded in 1960 as a member of the AFL, winning 2 championships in the league in 1964 and '65. Made the playoffs just one time in the 1970s, despite having OJ Simpson at running back. Were an excellent team from the late 1980s to the late 1990s, with 10 playoff berths in 12 years. These teams were led by 2 hall of famers who never won a championship- quarterback Jim Kelly and coach Marv Levy. Buffalo went to 4 straight Super Bowls from 1990-93, losing everyone. The first was lost on a missed field goal by Scott Norwood. The Bills have not made the playoffs since 1999, despite assembling some talented players in recent years.
"The Buffalo Bills with a chance to win the Super Bowl, down 20-19 to the Giants. Norwood, from 47 yards out. His kick is up, it's long enough, but it's no good! Wide right!"
by Sports Info July 03, 2006
An NFL team that must delight in torturing their fans with near playoff caliber teams. Known for prodigious amounts of talent, but with either a weak link or dream-shattering crises of confidence.
The Buffalo Bills would be great if Trent Edwards could show a little more heart, or if Turk Schonert could call a game worth a damn.
by Spaghetty December 12, 2008
single handedly the coolest football team in the NFL. Lost 4 straight Super Bowls in the 1990's. But the more important thing is that they MADE IT to 4 straight Super Bowls....and people still say that they sucked. Lets see the Dolphins or Patriots make it to 4 straight.
Oh yeah, they had OJ Simpson playing for them as their star player too!
JP Losman in 2005 all the way!
Oh yeah, they had OJ Simpson playing for them as their star player too!
JP Losman in 2005 all the way!
by falconbox530 May 22, 2005
the sickest losing team in the NFL. Nobody hates them except for those wankers in New York City and Boston. Fuck them! they've never won a superbowl, but they made the Superbowl 4 times in a row. The fans still love em cuz they try their hearts out every year. they always fall one game short of the playoffs, or one field goal short of Superbowl championships, one kick return TD of...
bills fan1: what are the bills, 9-7
bills fan2: ya, think so. didn't make the playoffs again
bills fan1: oh well, better luck next year. lets go watch a sabres game.
bills fan2: FUCKINEH
buffalo bills kick ass
bills fan2: ya, think so. didn't make the playoffs again
bills fan1: oh well, better luck next year. lets go watch a sabres game.
bills fan2: FUCKINEH
buffalo bills kick ass
by 12345432112345 December 21, 2006
A male who sometimes puts his penis in between his legs to reveal just a triangle of pubic hairs and pretends he is a lady. Often doing this act while dancing to 80's music in a psycadellic robe.
by Cristal Connors September 08, 2003
Finger-banging a girl with buffalo wing sauce still under your fingernails.
We had a lovely evening. I took her out to Buffalo Wild Wings, karaoke, then we retired. When things started getting 'hot', so did her vagina--because the wing sauce under my fingernails got rubbed on/into it. I 'Buffalo Billed' her.
by Ling Blinger February 27, 2013

subset: commoncrawl


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by Banago
Clutch with fold-over, magnetic closure. Embroidered allover pattern, unlined.
- 90% Wild Grass, 10% Palm Leaf
- 12" x 2" x 9"
- Hand crafted by artisans in the Phillippines
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RICHMOND, Va. (AP) — An American contractor detained in a contract dispute in Afghanistan was released Friday and three U.S. congressmen who complained about his detention said he had been seized without charges and beaten.
U.S. Reps. Scott Rigell and Frank Wolf of Virginia and Duncan Hunter of California sent a letter asking Secretary of State John Kerry to intervene for David Gordon, 38, of Virginia Beach, Va.
The congressmen said Gordon was detained Wednesday in a contract dispute but had not been charged. They said Gordon was injured in a beating but was not taken to an infirmary until the next day. Afghan authorities had asked for $2.4 million to release him, according to the legislators.
A spokesman for the U.S. Embassy in Kabul, John Rhatigan, said the Afghan government released Gordon on Friday, but he declined to comment on the demands.
"We continue to provide consular assistance as his attorney works to resolve this matter," Rhatigan said, without providing additional details.
Gordon works for northern Virginia's Tamerlane Global Services Inc.
The company's senior counsel, Ryan Kelley, said he talked to Gordon on Friday and said he was relieved he was free after what Kelley called a "terrible ordeal."
Gordon was attacked the same night he was taken into custody, leaving him bruised and with cuts requiring stitches, Kelley said.
"He was directed out into a yard and blindsided by someone and struck, it sounds like a number of times," Kelley said. "He was then put back into his holding cell with a bunch of people who committed crimes."
Kelley said Gordon, a diesel mechanic with a pregnant wife and two children at home in Virginia, was caught in "that bad behavior" even though he had no connection with a project that Tamerlane project that is the focus of a federal court case in Virginia. Gordon was leading a project to install satellite tracking devices on fuel trucks for the U.S. Department of Defense to prevent theft.
Tamerlane, which is based in Reston, is involved in logistics and cargo management in developing countries, including Afghanistan.
Kelley, who declined to give Gordon's location, said he would require additional medical treatment. He did not know the full extent of his injuries. He said his treatment in Kabul was cursory.
"He was under armed guard with six police officers who insisted on bringing him back to the jail. He wasn't full evaluated," Kelley said.
Tamerlane appealed to the lawmakers because they considered Gordon's plight "a matter of life and death," Kelley said.
An Associated Press telephone call to a listing for a David Gordon in Virginia Beach was not answered.


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Ever since the beginning of its most recent oil boom in 2005-06, Azerbaijan has been posting record-high economic growth rates, averaging at nearly 20 percent annually. This is not the first instance when fortunes are made from Azerbaijan's oil. At the beginning of the 20th century, Azerbaijan was, for a short time, the world's leading petroleum producer, producing more than half of the world's total output.
In the recent years Azerbaijan's economy has experienced some of the highest economic growth rates in the world. In 2000, the country's GDP was US$5.3 billion. In 2005 it was $13.2 billion, in 2008 $46.4 billion and by 2010 it was estimated to be $54.4 billion (which corresponds to $90.4 billion in purchasing power parity terms).[1]
Take a close look at Azerbaijan's economic boom though and the figures tell a more troubling story.
Table 1: Total oil production in Azerbaijan, thousand barrels per day, 2000-2010[2]
Source: U.S: Energy Information Administration
As Table 1 shows, oil production in Azerbaijan has experienced very fast growth since 2005. Today, with over 1 million barrels of oil produced daily, Azerbaijan is the world's 20th-largest oil producer. By comparison, Russia, which ranks first, produces 9.5 million barrels of oil per day, Saudi Arabia 8.3, Norway 2.1, Libya 1.7, and the UK, which ranks no. 19, 1.3 million barrels per day. [3]
Table 2: Net exports of oil in Azerbaijan, thousand barrels per day, 2000-2010[4]
Source: U.S: Energy Information Administration
Not only is Azerbaijan an important oil producer, but it also exports over 90 percent of the oil it produces. Azerbaijan's oil exports started growing from 1995 onwards, following the signing of the "Contract of the Century", which brought foreign direct investment by international oil companies into offshore oil exploration. However, as Table 2 shows, the steepest rise in the oil exports has taken place since 2005-2006. This was the time when the Baku-Tbilisi-Ceyhan pipeline became operational, supplying oil to Western markets. Nearly all Azerbaijan's exports are energy-related.
The rapid increase in Azerbaijan oil exports took place against the backdrop of a strong (although not uninterrupted) rise in oil prices over the past 10 years. Crude oil prices more than doubled from $24.54 per barrel in July 2001 to $57.58 in July 2005. After peaking at $145 in July 2008, they experienced a sharp drop in the second part of 2008, bottoming out at some $30 in December 2008. Since then, however, oil prices have recovered, passing the $100 threshold in January 2011.[5] Thus, over the past six years, Azerbaijan has been exporting more oil than ever before, and selling it at much higher prices. Taken together, these two developments explain why Azerbaijan's economy and budget have experienced such stupendous growth.
Table 3: Azerbaijan's exports, 2005-2009
Exports (total, million USD)
Energy share, percent
Source: International Trade Center, Index Mundi
(Note: the drop in the value of exports from 2008 to 2009 is due to the sharp drop in the oil price which took place during the global financial crisis. Since then, oil prices have recovered.)
Azerbaijan's new oil boom
The story of Azerbaijan's most recent oil boom began on 20 September 1994 when then president Heydar Aliyev signed a major deal with 11 international oil companies, The contract granted exploration and operation rights in the Azeri-Chirag-Guneshli (ACG) complex of Caspian Sea oil fields, situated some 120 km off the Azerbaijan shore. The deal was soon dubbed "the contract of the century' and is due to run until 2024.
Dr Hoşbakt Yusufzade,[6] a senior Azerbaijani geologist who was in charge of drawing up Azerbaijan's energy strategy, recalls the process leading to the decision on what to do with undrilled fields in the early 1990's:
"When the USSR collapsed, technology and money were needed to drill the Azerbaijani oil. We could either wait 30 years until we had the money and means or we would invite foreign companies. Aliyev chose the latter. There were people who objected. They said "we can do it ourselves." But it was a risky and expensive work and having international partners was a very good idea."[7]
Several months after the contract was signed, the oil companies formed the Azerbaijan International Operating Company (AIOC), an 11-strong consortium which included SOCAR, the Azerbaijan state oil company, and which was led by BP. The composition of the shares in the consortium reflected a wide range of national interests; BP gained the largest stake at 17.12 percent and second was Amoco from the US with 17.01 percent. Other companies included Russia's Lukoil (which would later sell its stake), Norway's Statoil, and Turkiye Petrolleri, the Turkish state oil company. Subsequently, Exxon and two Japanese companies joined AIOC as well.
AHTS Om & AHTS Islay: Anchor Pre-lay of Baku, Azerbaijan. Photo: British Petroleum
The contract signed with the Azerbaijani government was a Production Sharing Agreement (PSA) type. The agreement specified that the foreign companies would utilise their own resources, capital, technology and personnel, conducting exploration at their own risk. In case of success, the companies would use revenues from oil sales to compensate their investment costs and then share the profits with the government. It was estimated that $7.5 billion of Foreign Direct Investment would then flow into the country. According to the World Bank,
"The PSAs were the cornerstones of Azerbaijan's forthcoming development as they generated a significant amount of FDI in the country, raised demand in the economy, and generated confidence for future investments."[8]
The signing of the PSA was followed by concluding Joint Operating Agreements (JOA). These were made directly between the companies, to outline their rights, responsibilities and liabilities. The first, so-called "early" oil from Azeri-Chirag-Guneshli (ACG) fields was extracted in November 1997. It was exported via the newly refurbished pipeline to the city of Novorossiysk on the Black Sea coast of Russia. This route, however, was not sustainable for a number of reasons: Russia imposed high tariffs and mixed ACG Light crude oil with its own lower-grade oil before shipping. The admixtures negatively affected the price. According to one energy expert, the loss in price due to the mixing reached 4 to 5 USD per barrel.[9] (This was significant, given that the world crude oil prices fell precipitously in late 1997 and throughout 1998, from some 19 USD per barrel in November 1997 to approximately 10 USD per barrel in December 1998[10]). From Novorossiysk, the oil would have to be transported through the already very congested Bosphorus strait. Finally, the pipeline went through the territory of Chechnya. There was also a concern in Azerbaijan about the inherent dangers of Russia's monopoly on Azerbaijan's oil exports.[11]
In addition to the Baku-Novorossiysk pipeline, another pipeline was completed for transporting smaller amounts of "early oil" from Baku to the Supsa terminal on Georgia's Black Sea coast. However, just like the Novorossiysk pipeline, it had the disadvantage of creating the need to transport the oil through the busy Bosphorus. The combination of two pipelines provided a solution for smaller amounts of exports. For larger flows of oil, a different option was needed.
In 1998, an agreement was signed for the construction of a pipeline from Baku, via Tbilisi, the Georgian capital, to the Turkish port of Ceyhan on the Mediterranean. The initiative received a strong backing on the part of the United States, which valued the fact that the pipeline would bypass Iran. For Georgia and Azerbaijan it was important that the pipeline, which also bypassed Russia, would link them directly to Western markets.[12] The construction of the Baku-Tbilisi-Ceyhan (BTC) pipeline, which was to be financed by oil companies and not national governments) was delayed by the companies' doubts about the economic viability of the project, given its huge projected cost in excess of $3 billion (the actual costs of the BTC pipeline in the end amounted to $3.7 billion).[13] Given the plummeting oil prices, the oil companies were hesitant to make such large investments with uncertain returns. Gradually, however, wıth the rising oil prices and the upgraded estimates of the reserves in the ACG fields, the project became more attractive. In September 2002 construction started at Baku's Sangachal oil terminal.[14] Oil began to flow through the 1,760 km Baku-Tbilisi-Ceyhan pipeline, the second longest in the world, in June 2006.
By the end of that year, when one million barrels of oil a day were flowing from Baku to Ceyhan, it was already clear that economic diversification would be a major challenge for Azerbaijan. The 2006 report by consultancy MHC International LTD, "Converting Black Gold into Human Gold: Using Oil Revenues to Achieve Sustainable Development", analyzes the policy challenges facing single-resource economies, i.e., those that rely on the export of a single resource for the bulk of their foreign exchange earnings. The report compares and analyzes 40 such economies, taking an in-depth look at five of them. Norway (an oil producer) and Chile (a copper producer), which managed to fight the resource curse and diversify their economies, are taken as examples of success stories. Nigeria, a major oil producer, is a case study in failure, and Trinidad and Tobago, a small Caribbean oil and gas producing nation, is regarded as having "promising" potential. Finally, neighbouring Kazakhstan is examined as a case "still in the making." Both Kazakhstan and Azerbaijan, as relative newcomers to the league of energy exporters, face a largely similar set of challenges and problems. Their policy decisions and choices today would determine whether they would come to resemble the successful Norway and Chile or become a failure like Nigeria.
The report points out that, "being a major petroleum exporter does not mean that Azerbaijan is fully integrated into the global economy. At best, having oil revenues only gets Azerbaijan one foot in the door' of globalization."[15] It also goes on to note:
"There are inherent dangers in too rapid a rate of investment without the supporting institutional capacity to use resources effectively and efficiently, as well as significant policy and regulatory reforms." [16]
The report recommended the importance of facilitating the entry of the non-oil sector into the global economy and underlined this by saying that "it is in the non-oil sector where the vast majority of the Azerbaijan population lives and works, and those who must have the skills and opportunities to compete in the international economy"[17]. According to the report, the emphasis should be placed on human capital development and training, as well as on developing competitive export industries. This requires, the report concludes, the creation of "economic conditions where potential investors are not deterred by, for example, lack of access to export markets, entrenched monopolies or governance problems."
Resource curse
The resource curse' is a concept that describes the situation of countries with a strong dependence on extractive industries but with persistent and widespread low standards of living which are the direct result of corruption, a weak tax collection system and a lack of development in other sectors of the economy. The concept was introduced by Richard Auty in 1993. Resource curse usually occurs for three main reasons.[18]
The first reason, called "Dutch Disease" has to do with the difficulties created by the large influx of foreign exchange that the country receives for selling its natural resources. The inflow of money into the country leads to the appreciation of the exchange rate. A more expensive domestic currency means that the country's non-oil exports become more expensive (and thus less competitive) in the global markets, which dampens production in non-oil sectors. The presence of a high revenue-generating resource sector weakens incentives for entrepreneurs to develop small and medium enterprises in other sectors. This, in turn, thwarts the development of a strong middle class and results in growing social inequality. Other common attributes of Dutch Disease are excessive government spending and a real estate and construction boom.
The second reason is the negative effects of volatility of earnings. Natural resource prices are prone to considerable fluctuations. If a country draws most of its revenues from selling natural resources, the volatility will result in difficulties in budget planning and debt management.
Finally, a third and arguably the most important reason is institutional. The ready access to a large amount of funds reduces the willingness of the government to implement much-needed, yet politically unpopular reforms. Because a resource-rich state does not have to rely primarily on tax revenues to fill its budget, power holders lack incentives to set up effective institutions that guarantee property rights, provide good service, or foster accountability. Those in decision-making positions control the process of revenue distribution and will choose less oversight over more. As it has been the case in Azerbaijan, instead of building strong effective institutions, political elites will use "favours" to secure loyalty and obtain legitimation.
The institutional component in the resource curse has been strongly stressed by Terry Karl, who studied the concept of "the paradox of plenty." He describes the rentier state created by natural resource windfalls as an obstacle to political change:
"Dependence on petroleum revenues produces a distinctive type of institutional setting, the petro-state, which encourages the political distribution of rents. Such as state is characterized by fiscal reliance on petrodollars, which expands state jurisdiction and weakens authority as other extractive capabilities wither. As a result, when faced with competing pressures, state officials become habituated to relying on the progressive substitution of public spending for statecraft, thereby further weakening state capacity."[19]
There are some successful cases of resource-rich countries, both developed (such as the UK and Norway) and developing (Botswana, Chile and Malaysia), that managed to avoid or at least minimize the negative consequences of the "resource curse". However, these have been the exception rather than the rule.
Azerbaijan and the resource curse
Azerbaijan's oil boom, which began in 2006, is still a relatively recent development. Growth rates have been high but for the first several years there were no significant improvements in poverty alleviation. This has improved in the past several years, although the precise decrease in the poverty rate is difficult to measure and serious questions have been asked about the quality and reliability of official statistics. In any case, this has been achieved primarily through government social transfers. Despite generating high revenues, the oil and gas sector employs less than 1 percent of the population and thus is not a major factor behind improving job growth.
There have been signs of Dutch Disease in Azerbaijan: real estate prices have been rising, the non-oil sector remains small, and inflation has remained substantial. The annual average growth of the Consumer Price Index was 9.6 percent in 2005, 8.3 percent in 2006, 16.7 percent in 2007, reaching 20.8 percent in 2008.[20] The situation improved in 2009, but the following years again showed price rises.
The negative effects of the oil boom are most strongly felt in the institutional sphere Here Azerbaijan exhibits a typical range of behaviors and problems common for countries afflicted with a resource curse. These include persistent corruption, non-transparent government spending, and use of resource rents to keep unaccountable political elites in power. In addition to engaging in massive social transfers, the Azerbaijani leadership has gone on a military spending spree. Azerbaijan has been involved in a territorial dispute with Armenia over the Nagorno-Karabakh region and adjacent territories. According to the Swedish think tank Stockholm International Peace Research Institute, Azerbaijan's military expenditure more than doubled from $554 million in 2005 to $1,138 million in 2006 and has reached $1,421 million in 2010 (figures are given in constant 2009 dollars).[21] As a percentage of the GDP, this represents an increase from 2.4 percent to 3.4 percent. The Azerbaijani authorities provide even higher figures. In October 2010, the Azerbaijani parliament approved a military budget of $3.12 billion.[22]
The logo of the Azerbaijan State Oil Fund (SOFAZ)
Azerbaijan has been commended for taking two steps towards fighting the resource curse. The first one, taken in December 1999, was to set up a sovereign wealth fund called the State Oil Fund of Azerbaijan (SOFAZ), into which the revenues from oil exports have been channeled. The main aim of SOFAZ is to accumulate, save and efficiently manage oil revenues, investing them in bonds and stocks to generate interest for the benefit of future generations. By taking massive oil income out of the economy, SOFAZ is also supposed to help prevent the overheating of the economy and avoid high inflation rates. In reality, however, significant amounts of money from SOFAZ have been transferred to the state budget annually, in particular from 2008 onwards (see Table 4).
Table 4: State Oil Fund's transfers to the state budget in 2006-2011 (in million AZN[23] and in million USD)[24]
2012 (approved budget)
Amount in million AZN
Amount in million USD (converted)
In addition to direct budgetary transfers, SOFAZ funds a number of national projects including obtaining an equity share in the BTC oil pipeline, construction of housing for refugees, large scale irrigation projects, construction of the Baku-Tbilisi-Kars railway, and a study abroad programme for young Azerbaijanis.[28]
To give an example of the level of expenditures: in 2010 the Oil Fund received oil and gas revenues on the order of ca. 12.3 billion EUR. Out of this amount some 5.6 billion EUR was transferred to the state budget and an additional 448 million EUR was spent on national projects, according to SOFAZ data.[29] From 2001 until 2007, the assets of the Oil Fund increased from 491.5 million USD to 2475 million USD. Then, within the following year, the assets more than quadrupled to 11 billion USD.[30] As of July 2011 Azerbaijan SOFAZ's total assets were estimated at 30.2 billion USD.[31]
The second measure for which Azerbaijan has been commended was to join the Extractive Industries Transparency Initiative (EITI) in June 2003. The main aim of the initiative, which had been announced by then-UK Prime Minister Tony Blair in 2002 and which is currently in place in a number of resource-rich states, is to provide support for "improved governance in resource-rich countries through the verification and full publication of company payments and government revenues from oil, gas and mining."[32]
In November 2004, Azerbaijan signed the Memorandum of Understanding on EITI Implementation in Azerbaijan. In February 2009, Azerbaijan was judged to be EITI-compliant. The country's compliance has to be revalidated within a 5-year-period (i.e. by February 2014).[33] The first Validation Report for Azerbaijan in February 2009, contained the following overall assessment:
"The most notable, yet simple achievement of the initiative is that the public reporting of revenues from the oil and gas industry, which did not occur in Azerbaijan before the EITI, has now become routine."[34]
Semi-annual and annual reports on EITI produced by the government and by independent accountants are published on the SOFAZ website.
However, EITI does not demand transparency on how the revenues from the oil and gas industry are spent. It only requires companies to publish the payments they make, and governments to publish the payments they receive.[35]
Without transparency mechanisms in place, the funding of national projects creates a fertile ground for corruption. A leading Azerbaijani economic think tank, the Center for Economic and Social Development (CESD), conducted a monitoring study on the use of SOFAZ funds to build houses for refugees from the Nagorno-Karabakh conflict. The results pointed to "severe" problems with the use of public funds, to the extent of 50 million USD misappropriated within a single year. As the study found,
"Once the price of houses constructed within the project was compared with the market price, it was evident that the houses had been artificially overpriced. And another problem is substandard work during the construction process thus aiming to consume few funds, but overprice the project."[36]
By not addressing government spending, which is where the real problem lies, EITI fails to increase the accountability of the government.[37]
The SOFAZ also suffers from a lack of strategic vision. According to a CESD report,
"Money from the Fund is currently being spent with no strategy or criteria to measure the effectiveness of the spending decisions against alternative ways of using the Fund."[38]
All in all, EITI and SOFAZ taken together have had limited impact on the fundamental problems associated with the resource curseToday over 90 percent of FDI goes to the oil sector. Agriculture, which employs some 40 percent of the population, remains neglected. The growth in the non-oil sector has been sluggish, with the exception of the construction sector. There is no parliamentary oversight over the spending of the country's enormous hydrocarbon wealth. The rapidly increasing government expenditures fuel inflation and, due to the lack of transparency, breed corruption.
Natural Gas and Azerbaijan's potential contribution to European energy security
With the discovery of the offshore Shah Deniz gas field, the largest one in the country, in 1999, Azerbaijan was placed on track to also becoming an important gas producer. Shah Deniz began producing in 2006. Before that, there had been only small gas fields in Azerbaijan, previously a natural gas importer. Shah Deniz is operated jointly by BP, Statoil and a number of other partners, including Azerbaijan's SOCAR, Russia's Lukoil, Iran's NIGC and France's Total.
Since July 2007 natural gas from Shah Deniz has been processed at the Sangachal terminal and transported to Georgia and to Erzurum, in eastern Turkey, along the South Caucasus Pipeline. This gas pipeline was built along the Baku-Tbilisi-Ceyhan oil pipeline, which allowed to lower its cost due to economies of scale. Complicated negotiations about the amount and the price of the gas Azerbaijan sells to Turkey have been continuing ever since. Azerbaijan produced approximately 27 billion cubic meters (bcm) of natural gas in 2010 and exported it to four countries: Turkey, Georgia, Russia and Iran. Turkey continues to purchase six billion cubic metres of gas a year. For 2011, Russia's Gazprom signed a contract with Azerbaijan allowing it to buy two billion cubic metres of gas double the amount contracted in 2010 (although Russia ended up importing less gas that year, as the contracts allow for changing the actual supply volume). In December 2011 Gazprom announced its agreement with SOCAR to boost gas imports to 3 bcm in 2012.[39] Georgia buys one billion cubic metres of gas from Azerbaijan annually. In January 2011, Azerbaijan signed a five-year gas supply contract with Iran, envisioning at least 1 bcm of natural gas exports annually.[40]
Stage 2 of the Shah Deniz field development is yet to be implemented. It envisages the construction of new offshore platforms, subsea wells, an expansion of the Sangachal Terminal and of the South Caucasus Pipeline. [41] BP and Statoil are the leading companies in charge of operating this field, in partnership with five other companies. Shah Deniz II is expected to start producing in 2017. Azerbaijan's natural gas potential conitnues to grow: in September 2011 Socar and France's Total announced a major gas natural discovery in the so-called "Absheron X-2" well in the Caspian some 100 km southeast of Baku, with estimated reserves of 350 bcm of natural gas.[42]
From projects currently in operation, Azerbaijan is expected to produce 30 billion cubic meters per year between 2011 and 2014. When fully up and running Shah Deniz Stage 2 is expected to add another 16 billion cubic metres per year (including 10 bcm earmarked for European markets). According to SOCAR's estimate, Azerbaijan will have 25 to 30 bcm of gas available for export by 2020-2025. From 2025, Azerbaijan's gas production is expected to reach 50 bcm annually. Natural gas sales will thus play an increasingly important role in Azerbaijan's economy. According to CESD Chairman Vugar Bayramov, revenues from sales of gas are expected to exceed oil revenues in the government budget already from 2015 onwards.[43]
Bringing Caspian gas to the EU: pipeline rivalry
In November 2008, the European Commission, wary of the EU's dependence on Russian energy imports, proposed the "Southern Gas Corridor" strategy aimed at bringing Caspian and Middle Eastern gas to Europe. It was announced that the creation of the Corridor was "one of the EU's highest energy security priorities."[44] As an important gas supplier, Azerbaijan plays a decisive role in the success of the Southern Corridor. So far, four projects have been included in the Southern Gas Corridor and none of them would be viable without Azerbaijan's participation.[45]
The first and the most ambitious one is Nabucco, which envisions the construction of a large pipeline with a capacity of 31 billion cubic meters (bcm) per year, with a possibility of doubling. The pipeline would bring gas from the Turkish-Georgian and Turkish-Iraqi borders, crossing the territory of Turkey, Bulgaria, Hungary and Romania and arriving at Baumgarten, Austria. The Nabucco consortium includes Germany's RWE, Austria's OMV, Hungary's MOL, Romania's Transgaz, Bulgaria's Bulgargaz and Turkey's Botas. The costs are estimated at 7.9 billion EUR. However, in February 2011 The Guardian disclosed information according to which BP's own estimate of the costs was nearly double the amount put forward by Nabucco's Austrian management some 14 billion EUR vs 7.9 billion.[46] Aside from cost considerations, the key problem with Nabucco is the lack of a secure second supplier. Azerbaijan alone would be unable to fill the entire 31 bcm capacity of the envisioned pipeline, given its existing sales commitments to other countries. Therefore, being able to include gas from other sources such as Turkmenistan, Iran or North Iraq may be crucial but difficult to implement for political and security reasons.
The Shah Deniz Alpha gas platform in the Caspian supplies gas to Europe via a pipeline through
Azerbaijan, Georgia and Turkey. Photo: British Petroleum
The second project is the Interconnector Turkey-Greece-Italy (ITGI) involving Italy's Edison, Greece's DEPA and Turkey's Botas, The project relies on expanding the existing pipeline between Turkey and Greece by adding a section connecting it to Italy. The planned capacity is 8 bcm, and the estimated cost is 1.5 billion USD.
Third is the Trans-Adriatic Pipeline (TAP) which involves Norway's Statoil, EGL from Switzerland and Germany's E.ON Ruhrgas. The TAP project proposes the construction of a pipeline from Greece to Albania and Italy, with a capacity of approximately 10 bcm, at the cost of some 2 billion USD. Fourthly, there is also the less popular White Stream project which was proposed by Ukraine. White Stream envisages building a pipeline branching off the South Caucasus Pipeline and crossing the Black Sea from Supsa, passing through the Crimea to Constanta in Romania.
In addition to these projects, there is another smaller, Romanian-backed project called AGRI Azerbaijan-Greece-Romania Interconnector. The AGRI project envisages transporting natural gas from Azerbaijan to Georgia's Black Sea coast via pipeline, liquefying it at a special terminal and delivering the liquefied natural gas (LNG) by tankers to Romania's port of Constanta on the Black Sea. AGRI has recently requested to be included in the Southern Gas Corridor. The talks in Brussels on this issue are scheduled for early 2012.
Much of the current debate revolves around the Shah Deniz Consortium's long-anticipated choice of pipeline for the 10 bcm of natural gas that is supposed to come from Shah Deniz II from 2017. By the deadline of 1 October 2011, three of the Southern Corridor pipelines Nabucco, TAP and ITGI - have submitted bids for the transport of Shah Deniz II gas to Europe. Almost at the last moment in September 2011 British Petroleum proposed yet another option the South East European Pipeline (SEEP). The details of the proposal have not been hammered out yet, but it would strongly rely on using the existing regional networks enhanced with interconnectors, thus significantly lowering the costs as compared to Nabucco. The SEEP was also included in the bid.[47]
So far, Azerbaijan has been trying to steer an independent course between the pipeline rivalries and has been wary of committing too early to any of the proposed projects. It has not been fully satisfied with the three pipeline proposals, which did not sufficiently provide for Azerbaijan's interests. In addition, it has also been Azerbaijan's strategy to keep several different buyers for its gas.[48]
Things gained speed on 25 October 2011 when Azerbaijan and Turkey signed agreements on Azerbaijani gas exports to Turkey and on gas transit to Europe via Turkey. The agreements established legal and commercial terms for direct transactions between Azerbaijan and European buyers, paving the way for Shah Deniz II gas to Europe.[49] Building on this agreement, in a strategic move in November 2011 Azerbaijan's and Turkey's energy ministers announced plans to construct the Trans-Anatolian Gas Pipeline (also known as Trans-Anadolu, or TANAP) that would cross Turkey from east to west and transport some 16 bcm gas annually. Out of this amount, an estimated 6 bcm will be reserved for Turkey's domestic consumption (or re-export), and the rest would be exported to Europe.[50] The two countries signed a memorandum of understanding on the construction of the TANAP on 26 December 2011 in Ankara.
The agreement to construct the TANAP still leaves open the question of how to bring Caspian gas from the Turkish coast to Europe. Analysts are debating the full implications of the announced pipeline, but it is already clear that it would make the construction of the full-length Nabucco pipeline redundant. However, as Jamestown Foundation Senior Analyst Vladimir Socor argues, a shortened (and cheaper) Nabucco running from the Turkish border to Europe would nevertheless be a feasible option.[51] In any case, by signing the agreement on TANAP, Azerbaijan and Turkey not only cemented their strategic relationship, but also strengthened their respective positions in negotiating the terms of Caspian gas exports to the EU in the future.
The deadline for announcing the decision on the definitive choice of the pipeline for Shah Deniz II gas has been postponed several times. The consortium has already identified TAP (rather than ITGI) as the preferred way of gas transportation to Italy. By June 2012, the consortium is expected to decide on the "semifinalist" pipeline to transport gas to central and southern Europe. Finally, by October 2013 the final decision on which route to choose for Shah Deniz II gas whether the route through the Southern Balkans to Italy or a route to southern and central Europe shall be made. [52]
Further Reading
- Vladimir Socor, "Trans-Anatolia Gas Pipeline: Wider Implications of Azerbaijan's Project," Eurasia Daily Monitor vol. 9, issue 3 5 January 2012.
- More detailed information on Azerbaijan's economic structure can be found in the Economist Intelligence Unit (EIU) quarterly reports,
- To learn more about the link between post-Soviet Azerbaijan's development and its oil wealth, read David I. Hoffman's 2007 article "Oil and Development in Post-Soviet Azerbaijan".
- EIA, "Country Analysis Briefs Azerbaijan", last updated in January 2012.
- Oksan Bayulgen, Foreign Investments and Political Regimes: The Oil Sector in Azerbaijan, Russia, and Norway. Cambridge University Press, 2010.
- Steve LeVine, The Oil and the Glory: The Pursuit of Empire and Fortune on the Caspian Sea, Random House, 2007.
- The most recent annual report on EITI in Azerbaijan (for 2010)
- On the effectiveness of using oil revenues, see an article by Azerbaijani economic think tank Center for Economic and Social Development: Vugar Bayramov, Tim McNaught, Elchin Rashidov, "Managing Resource Revenues in Oil-Rich CAREC Countries: The Case of Azerbaijan", CESD, Baku, April 2011.
On the resource curse:
- Richard M. Auty, Sustaining development in mineral economies: the resource curse thesis (Routledge, 1993).
- Richard M. Auty, "Natural Resources, Capital Accumulation and the Resource Curse", Ecological Economics, no. 61 (2007): pp. 627-634.
- Jeffrey D. Sachs and Andrew M. Warner, "Natural Resources and Economic Development: The curse of natural resources", European Economic Review 45 (2001): pp. 827-838.
- Gylfason, Thorvaldur, "Natural resources, education, and economic development", European Economic Review 45 (2001): 847859.
- George Soros, "Lifting the Resource Curse", Project Syndicate, 15 March 2003.
- Svetlana Tsalik, "Caspian Oil Windfalls: Who Will Benefit?" (with a foreword by Joseph Stiglitz). Caspian Revenue Watch/ Open Society Institute, 2003.
- Terry Lynn Karl, The Paradox of Plenty: Oil Booms and Petro-States. Los Angeles, University of California Press, 1997.
[1] Based on IMF data for Azerbaijan, http://www.imf.org/external/pubs/ft/weo/2011/01/weodata/weorept.aspx?sy=2000&ey=2010&scsm=1&ssd=1&sort=country&ds=.&br=1&c=912&s=NGDPD percent2CPPPGDP&grp=0&a=&pr1.x=63&pr1.y=5
[2] U.S. Energy Information Administration (http://www.eia.gov/cfapps/ipdbproject/iedindex3.cfm?tid=5&pid=53&aid=1&cid=regions&syid=2000&eyid=2010&unit=TBPD).
[3] Huffington Post, "Top 20 Oil-Producing Countries", 22 February 2011, http://www.huffingtonpost.com/2011/02/22/oil-producers-exporters-t_n_826564.html#s244298&title=20_Azerbaijan
[4] U.S. Energy Information Administration, http://www.eia.gov/countries/country-data.cfm?fips=AJ#undefined
[5] Index Mundi, Crude Oil (petroleum); Dated Brent Monthly Price - US Dollars per Barrel. http://www.indexmundi.com/commodities/?commodity=crude-oil-brent&months=300
[6] Born in 1930, Prof Dr Yusufzade graduated in Geology, was a member of the Communist Party, and was the leading name in exploration and production of oil and gas in Soviet Azerbaijan. When Heydar Aliyev became president, he recruited Yusufzade to prepare the country's energy strategy
[7] Yusufzade, presentation at the Azerbaijan Diplomatic Academy's Summer Energy School, Baku, 5 July 2010.
[8]World Bank, Azerbaijan Country Brief 2009, "Economy", November 2009. http://web.worldbank.org/WBSITE/EXTERNAL/COUNTRIES/ECAEXT/AZERBAIJANEXTN/0,,contentMDK:20174399~menuPK:301921~pagePK:141137~piPK:141127~theSitePK:301914,00.html
[9] Jonathan Elkind, "Economic Implications of the Baku-Tbilisi-Ceyhan Pipeline", in The Baku-Tbilisi-Ceyhan Pipeline: Oil Window to the West, eds. S. Frederick Starr and Svante Cornell (Washington DC, 2005), p. 46.
[11] Svante Cornell, Azerbaijan since Independence (M.E. Sharpe, 2011), pp. 226-227.
[12] Thomas de Waal, The Caucasus: An Introduction (Oxford University Press, 2010), p. 180.
[14] Thomas de Waal, The Caucasus: An Introduction, p. 178.
[18] See Brookings, "Central Asia's Energy Challenge: Overcoming the Natural Resource Curse", 11 August 2008. http://www.brookings.edu/opinions/2008/0811_central_asia_linn.aspx
[19] Terry Lynn Karl, The Paradox of Plenty: Oil Boom and Petro-States (University of California Press, 1997): p. 16.
[20] Data taken from the Central Bank of Azerbaijan, "Statistics", http://www.cbar.az/assets/92/main_macroeconomic_indicators.pdf
[21] SIPRI, "Military Expenditure Data Azerbaijan", http://milexdata.sipri.org/result.php4
[22] Shahin Abbasov, "Azerbaijan: Baku Embarks on Military Spending Surge, Seeking Karabakh Peace", Eurasia Insight, 22 October 2010. http://www.eurasianet.org/node/62223
[23] Data for 2003-2009 taken from SOFAZ, "Annual Report 2009", p. 26. http://www.oilfund.az/pub/uploads/5YR64gGt.pdf
[24] The amounts in USD are calculated on the basis of the historical exchange rates available from the website of the Central Bank of Azerbaijan, http://www.cbar.az/other/azn-rates
[25] SOFAZ, "SOFAZ Revenue and Expenditure Statement for 2010," http://www.oilfund.az/en/account/93
[26] SOFAZ, " SOFAZ 2011 budget amended", http://www.oilfund.az/en/content/24/277
[27] SOFAZ, "SOFAZ 2012 budget approved", 30 December 2011, http://www.oilfund.az/en_US/hesabatlar-ve-statistika/buedce-melumatlari/ARDNF-budce-tesdiq-edildi.asp
[28] SOFAZ, "FAQ", http://www.oilfund.az/en/content/21/85. The annual funding for the study abroad programme usually ranges between roughly 10 and 15 million EUR (see data on the SOFAZ website).
[29] SOFAZ, "SOFAZ Revenue and Expenditure Statement for 2010," http://www.oilfund.az/en/account/93
[30] SOFAZ, "Annual Report 2009", p. 8. http://www.oilfund.az/pub/uploads/5YR64gGt.pdf
[31] Sovereign Wealth Fund Institute, "Sovereign Wealth Fund Rankings", July 2011, http://www.swfinstitute.org/fund-rankings/ .
[33] EITI, Azerbaijan. http://eiti.org/Azerbaijan
[34] Coffey International Development in association with IPAN and PKF, "Validation of the Extractive Industries Transparency Initiative (EITI) in the Republic of Azerbaijan" report (Feb. 2009), p. 24. http://eiti.org/files/Azerbaijan percent20EITI percent20Validation percent20Report.pdf
[35] EITI; "EITI Factsheet", 3 May 2011. http://eiti.org/files/2011-05-03_English_FactSheet.pdf
[36] Center for Economic and Social Development, Ending Dependency: How Is Oil Revenue Effectively Used in Azerbaijan?(2008), p. 60.
[37] See, for example, Julia Gouseva, "EITI: a new global standard for lying", Open Democracy, 11 September 2008. http://www.opendemocracy.net/article/yes/eiti-a-new-global-standard-for-lying
[38] CESD, "Management of Oil Revenues in Azerbaijan: Transparency and Effectiveness", 2011, p. 1. http://www.cesd.az/documents/paper_eng.doc
[39] Interfax, "Gazprom to boost gas purchases in Azerbaijan to 3 bcm in 2012 (Part 2)", 15 December 2011. http://www.interfax.com/newsinf.asp?id=295704
[40] Bloomberg, "Azerbaijan Signs Gas Supply Contract With Iran Before EU Visit", 12 Jan 2011. http://www.bloomberg.com/news/2011-01-12/azerbaijan-signs-gas-supply-contract-with-iran-before-eu-visit.html
[41] BP Caspian, "Shah Deniz", http://www.bp.com/sectiongenericarticle.do?categoryId=9006668&contentId=7015092
[42] Total, "Azerbaijan: Total makes a major gas discovery in the Caspian Sea", 9 September 2011. http://www.total.com/en/about-total/news/news-940500.html&idActu=2636
[43] CESD, "Should Azerbaijan say "no" to the Nabucco pipeline project?", 28 May 2011. http://cesd.az/new/2011/05/should-azerbaijan-say-no-to-nabucco/
[44] European Commission, "Second Strategic Energy Review. An EU Energy Security and Solidarity Action Plan" (COM/2008/781), Brussels, 13 November 2008. http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CELEX:52008DC0781:EN:NOT
[45] For a good overview of the Southern Corridor projects and Azerbaijan's position, see "Azerbaijan will decide the shape of the Southern Gas Corridor", Eastweek, 19 Jan 2011, http://www.osw.waw.pl/en/publikacje/eastweek/2011-01-19/azerbaijan-will-decide-shape-southern-gas-corridor
[46] The Guardian, " European gas pipeline costs double", 20 February 2011. http://www.guardian.co.uk/business/2011/feb/20/european-gas-pipeline-nabucco-costs-double
[47] Vladimir Socor, "South-East Europe Pipeline: A Downsized Nabucco Proposed By BP", Eurasia Daily Monitor, Volume: 8 Issue: 202, 2 November 2011. http://www.jamestown.org/single/?no_cache=1&tx_ttnews[tt_news]=38609&tx_ttnews[backPid]=512
March 2011
Generation Facebook on trial
The country Heydar Aliyev built
Oil and Democracy under Ilham Aliyev
Baku dissidents


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podcasts that play JBE
Carnal Knowledge Podcast
Charles Hodgson is an author and podcaster and has a checkered history: engineering, whitewater canoeing, space hardware, skate-skiing, electronics, environmentalism, dot-com, writer and wordlover. Charles has also written a book called Carnal Knowledge due out in October 2006
X Pat Radio
British ex-pat on the air with lots of podsafe music and a few friends drop by once in a while.
Five Gallon Podcast
Hosted by Corey and Amy, this typically hour long weekly podcast delivers podsafe indie music submitted by artists and bands from around the globe! With an always odd assortment of 'Five Gallon Panelists' co-hosting live in studio, or via Skpe, this show is bound to bring you an earbud full.
An tImeall
Podcasting from the Margin. An Audio Blog in the Irish Language.
The Procrasticaster is no slave to productivity despite the temptation. Got stuff to do? Set it aside for later and take a little time to enjoy life first.
New Jersey Jamcast
Rob Usdin has been involved in radio and Computing for more then 15 years. He's played support the truth on his show #8.
The Mike and Michelle Show
Chicago native Boobs (Michelle) also has an erotic podcast called "Whispered Pearls". San Bernardino native Bat Rastard (Mike) has his own bent take on things. Together we bring out the worst in each other. Works for us.
Cast On Podcast
got an email from these podcasters about playing Stress. Hope to see us on their podcast soon.
Radical Reflections Podcast
10 years of radio experience, a lifetime of political dabbling, twenty minutes of prep time.
Middle Management Lobotomy Podcast
Kevin J. Williams, C.P.M., is currently a Director of Technology Solutions. His current role is to consult on streamlining the purchasing and payment processes through the use of technology.
I've seen Support the truth on their playlist recently.
I've seen Support the truth on their playlist recently.
The Big Break
From the same folks that bring you the Lowcountry Voice, comes The Big Break. A weekly podcast highlighting the best unsigned and independent label music artists. From beautiful Charleston SC.
Snowboarders Radio Show
Mountains, Snowboarding, Snow conditions, weather reports, Snowboarding equipment and Video reviews, music, but most of all the adventures of ordinaery snowboarders surfing Powder.
So - I saw WTFMFWTFAYT on their playlist - must have liked the screaming.
So - I saw WTFMFWTFAYT on their playlist - must have liked the screaming.
High Orbit
Music, news, and feedback from all over the quadrant.
Alternative teen music podcast
With you once a week to bring you music from the podsafe music network. I have a huge mix of genres but all the music is great! Listen and Enjoy!
RobKast Radio
PodSafe Music only, and collaboration of the auditors, with their own work
Suffolk and Cool
Podcast based in Suffolk UK drawing great new music from around the world.
A place for musicians and listeners to get together along with some fairly
quirky individuals from this "sleepy" backwater of the UK.
A place for musicians and listeners to get together along with some fairly
quirky individuals from this "sleepy" backwater of the UK.
Get Jacked
Play what I like.
Say what I like.
Show up when I like.
If there's money in this, I'll KISS Adam Curry
Say what I like.
Show up when I like.
If there's money in this, I'll KISS Adam Curry
Antecubital Liposuction
Antecubital Liposuction is funny, irreverant (or is that irrelevant), and a whole bunch of other weird adjectives. The closest mainstream comparison would be Dr Demento. Artists reminiscent of Weird Al Yankovic, Spike Jones, Ray Stevens, Cledus T. Judd, Frank Zappa, etc.
Top of the Podsafes!!!
The Real Top Hits, chosen by the people, for the people...so you have no excuse. Hits chosen from the top lists of the podsafe music network. (JBE has 2 songs this week!!!)
Voodoo Radio
I decided to get into podcasting after taking some time off from the whole internet radio thing. Stop on by our site and join in the fun. Call the FECK Line at 206-339-FECK. You wanna know more about the host? Listen in. Ask questions through the comment line or E-mail us @ voodooradio@gmail


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Tagged: oncourse
Fragmentary Course Data Thoughts… From XCRI-CAP1.2 to CourseData API?
A ten minute post, not thought through, just collecting together some thoughts arising from a Twitter exchange with @jmahoney127, @jacksonj04, @cgutteridge and @mhawksey that followed from picking up on a comment from Alan Paull re: the latest demo OU XCRI feed that I don't want to forget in the midst of doing other unrelated stuff today… (Additional fragmentary thoughts in that comment thread.)
Looking at the latest OU XCRI-CAP 1.2 feed, it seems to be a little bit richer than last time I looked:
Here's a snapshot of the University of Lincoln feed:
This represents a partial view of data available via the ONCourse API, I think?
Which leads to a couple of questions:
1) is all the data required to publish an XCRI-CAP1.2 feed available via the ONCourse API? That is, could I generate the XCRI feed from calls to the API?
2) what is available via the API that isn't in the XCRI feed?
3) could we create an API over the XCRI feed data that resembles (in part) the ONCourse API? That is, for an institution that has an XCRI-CAP 1.2 feed but no additional #coursedata development resources, could we create a simple JSON API layer that offers at least some of the ONCourse API functionality? And would the functionality/data that such an API could make available actually be rich enough or complete enough to actually do anything useful with?
Note: one of the advantages of the XCRI-CAP1.2 feed is that it can be used as a bulk transport format, a convenient source for a crude database of all the current (or future?) course offerings provided by an institution. It can also be though of as an XML database of an instition's course offerings.
Via @mhawksey, a link to a current CottageLabs XCRI demonstrator project, which in turn leads to a Github repo that includes an XCRI aggregator scraper (there is some sort of irony there…?) and an XCRI2JSON converter.
SOmething else that also comes to mind: A Developers' Guide to the Linked Data APIs that demonstrated the creation of RESTful, JSON producing APIs over Linked Data datasets.
Right… now for that other stuff…
PS via @alanepaull, JISC #coursedata programme blogs
Getting ONCourse Data Flowing into Google Spreadsheets
One of the challenges that needs to be addressed when developing data driven applications is how to get data from a data base to the point of use. Another relates to time-relevance. For example, in one document you might want to look at figures or data relating to a specific, fixed date or period (March 2012, for example, or the academic years 2012-13). At other times, you might want current data: values of some indicator over the last 6 weeks for example. Where live data feeds are available, you might want them to be displayed on a dashboard. In other circumstances, you might want a more traditional printed report or Powerpoint presentation, but one that contains absolutely up to the minute information. Ideally, the report or presentation would be "self-updating" so that each time you printed it off, it contained the latest data values.
One common user environment for data related activities is a spreadsheet. When developing an API that produces data that might be usefully manipulated within a spreadsheet context, it can be useful to provide a set of connectors that allow data to be pulled directly from the API and inserted into the spreadsheet.
Here's a quick example of how we might start to pull data into a Google Spreadsheets context from the University of Lincoln course data API. The example calls broadly reproduce those described in Getting ONCourse With Course Data.
Although the new script management tools in the Google Apps environment confuse the process of defining spreadsheet specific scripts, at its heart defining custom spreadsheet functions for Google Spreadsheets is a trivial exercise: create a custom function (for example, myFunction(val)), pass in a value (such as a cell value) and return a value or array. You can can call the function using a formula, =myFunction(A3), for example. If a single value is returned, this will be returned into the calling cell. If a one-dimensional list is returned, it will add alues to the current row. If a two dimensional array is returned, it will populate rows and columns.
Here are a few helper functions for calling the ONCourse data into a Google Spreadsheet:
function signed(url){ //Use this to add the API key, for example: //return url+'?key='+KEYVAL return url } function gurl(url){ //Fetch the JSON data and parse it as such raw=UrlFetchApp.fetch(signed(url)) json=Utilities.jsonParse(raw.getContentText()) return json } function jgrabber(u){ root='https://n2.online.lincoln.ac.uk' return gurl(root+u) } function grabModulesId(id){ path= '/modules/id/'+id json= jgrabber(path ) return json['result'] } function grabProgrammesId(id){ path= '/programmes/id/'+id json= jgrabber(path ) return json['result'] } function assessmentByModuleID(moduleID){ d=grabModulesId(moduleID) return d['assessments'] }
Let's now see if we can pull data into the spreadsheet, and try to get a feel for whether this sort of approach looks as if it may be useful…
First up, how about getting a list of programmes associated with a module?
function printProgsFromModuleID(moduleID){ d=grabModulesId(moduleID) var arr = []; c=[] c.push(d['title']) c.push(d['module_code']['code']) c.push(d['level']['description']) c.push(d['credit_rating'] + ' points') arr.push(c) arr.push([]) c=['Programme', 'Course', 'Course Code'] arr.push(c) for (var i=0;i< d['module_links'].length;i++){ r=d['module_links'][i]['programme'] c=[ r['programme_title'], r['course_title'], r['course_code']['code'] ] arr.push(c) } return arr }
Here's the result:
How about learning outcomes per module (via the assessments associated with each module)?
function learningOutcomesByModuleID(moduleID){ d=assessmentByModuleID(moduleID) arr=[] for (i=0; i<d.length; i++){ r=d[i] assessment=gurl(r['nucleus_url'])['result'] c=[ assessment['module']['title'], assessment['module']['module_code']['code'], assessment['assessment_method'] ] arr.push(c) learningOutcomes=assessment['learning_outcomes'] for (j=0; j< learningOutcomes.length; j++) arr.push([ '','', learningOutcomes[j]['description'] ]) } return arr }
Which gives us:
And how about programme outcomes for a particular programme, broken out into outcome types:
function programmeOutcomesByProgrammeID(id){ d=grabProgrammesId(id) arr=[] var types= new Object(); for (i=0;i<d['programme_outcomes'].length; i++){ r=d['programme_outcomes'][i] if (types[ r['category']['title'] ] == undefined ){ types[r['category']['title']]=[] } types[r['category']['title']].push(r['description']) } for ( j in types ) arr.push([j,types[j] ]) return arr }
The result? A handy table:
Okay, so that all seems easy enough. I think that Google docs are also scriptable, so it should be possible to populate a templated "word" document using data pulled from the API (for example, using a snippet like this one of Martin Hawksey's: Google Apps Script to fill in a Document template with Spreadsheet data).
One thing I realised about the API from playing with this recipe was that it is defined very much as a little-l, little-d "linked data" API that works well for browsing the data. The well defined URIset and use of internal unique identifiers make it easy to traverse the data space once you are in it. However, it's not immediately obvious to me how I could either search my way into the data, or access it via natural identifiers such as programme codes or module codes.
[Seems I missed a trick on the API front… As described in APMS -> Nucleus -> APIs. How? Why?, it seems that you could get details of all assessments that are the final assessment for the module, that contain group work at: https://n2.online.lincoln.ac.uk/assessments?access_token=ACCESSTOKEN&group_work=1&final_assessment=1]
For example, to print the programmes associated with a module, I might use the above formula =printProgsFromModuleID(97), but the identifier I need to pass in (97) is an internal, machine generated ID. This is all well and good if you are working within the machine-ID space, but this is not the human user space. For that, it would be slightly more natural to make use of a module code, and call something like printProgsFromModuleCode('FRS2002M'). There are issues with this approach of course, with module codes being carried over from presentation to presentation, and breaking a simple bijective (one-one onto) relationship between internal module IDs and module codes. As a result, we might need to further qualify these calls with a presentation year (or by default assume the presentation from the current academic year), or whatever other arguments are required to recapture the bijectivity.
PS in passing, here's another view over modules by programme, broken down into core and option modules.
There are a few problems with this view – for example, the levels need ordering properly; where there are no core or no optional modules the display is not as good as it could bel the label sizing is a bit small; there is no information relating to pre-requisites for optional modules – but it's a start, and it's reasonably clean to look at.
It should also be easy enough to tweak the data generator script to allow us to use the same display script to show assessment types for each module in a programme, as demonstrated using enclosure charts in VIsually Revealing Gaps in ONCourse Data , and maybe even learning outcomes too.
If I get a chance, I'll look through the sorts of thing requested in the ONCourse Focus Group – 14th March 2012 and try to pull out some views that match some of the requested ones. What would also be interesting would be to have a list of use cases from people who work with the data, too…
VIsually Revealing Gaps in ONCourse Data
One of the things that I never really, fully, truly appreciated until I saw Martin Hawksey mention it (I think in an off the cuff comment) at a JISC conference session a year or two ago (I think?!) was how we can use visualisations to quickly spot gaps, or errors in a data set.
Following on from my previous University of Lincoln course data explorations (see Getting ONCourse With Course Data and Exploring ONCourse Data a Little More… for more details), I have another little play, this time casting the output of course data around a programme into a hierarchical tree format that can be used to feed visualisations in d3.js or Gephi (code; call the data using URLs rooted on https://views.scraperwiki.com/run/uni_of_lincoln_oncourse_tree_json/ Parameters include: progID (programme ID using the n2 ID for a programme); full=true|contact|assessment (true generates a size attribute for a module relative to the points associated with the module; assessment breaks out assessment components for each module in the programme; contact breaks out contact hours for each module; format=gexf|json gives the output in GEXF format or d3.js tree JSON format. Note: it should be easy enough to tweak the code to accept a moduleID and just display a view for the assessment of contact time breakdown for the module, or a programme ID and level and just display the contact or assessment details for the modules in a particular level, or further core/option attribute to only display core or optional modules etc.).
I also did a quick demo of how to view the data using a d3.js enclosure layout. For example, here's a peek at how core and option modules are distributed in a programme, by level, with the contact times broken out:
The outermost bubble is a programme, the next largest bubbles represent level (Level 1, Level 2, etc corresponding to first year, or second year of an undergraduate degree programme etc). The structure then groups modules within a level as either core or option (not shown here? All modules are core for this programme, I think…?) and then for each module breaks out the contact time in hours (which proportionally set the size of contact circles) and the contact type.
The labelling is lacking in a flat image view, (if you hover over elements you get tooltips popping up, that identify module codes, whether a set of modules are core or option, the level of a set of modules etc., but in places the layout is hit and miss; for example, in the above example, one module must have 100% lectures, so we don't see a module bubble around it. I maybe need to see each module bubble with a dummy/null bubble of size 0, if that's possible, to force a contact bubble to be visibly enclosed by a module bubble?)
Here's another example, this time breaking out assessment types:
Hovering over these two images (click through them to see the live version), I noticed that form this programme, there don't appear to be any optional modules, which may or may not be "interesting"?
Looking at the first, contact time displaying image, we also notice that several modules do not have any contacts broken out. Going back to the data, the corresponding element for these modules is actually an empty list, suggesting the data is not available. What these views give us, then, is a quick way exploring not only how a programme is structured, but which modules are lacking data. This is something that the treemaps in Exploring ONCourse Data a Little More… did not show – they displayed contact or assessment breakdowns across a course only for modules where that data was available, which could be misleading. (Note that I should try to force the display of a small empty circle showing the lack of core or option modules if a programme has no modules in that category?)
Something else that's lacking with the visualisations is labeling regarding which programme is being displayed, etc. But it should also be noted that my intention here is not to generate end user reports, it's to explore what sorts of views over the course data we might get using off the shelf visualisation components, (testing the API along the way), how this might help us conceptualise the sorts of structures, stories and insights that might be locked up in the data and how visual approaches might help us open up new questions to ask over, or more informative reports to drawn down from, the API served data itself.
Anyway, enough for now. The last thing I wanted to try was pulling some of the API called data into an R environment and demonstrate the generation of a handful of reports in that context, but I've run out of time just now…
Exploring ONCourse Data a Little More…
Following on from my preliminary tinkering with the University of Lincoln course data API, I had a bit more of a play last night…
In particular, I started looking at the programme level to see how we might be able to represent the modules contained within it. Modules are associated with individual programmes, a core attribute specifying whether a module is "core" (presumably that means required).
I thought it might be interesting to try to pull out a "core module" profile for each programme. Looking at the data available for each module, there were a couple of things that immediately jumped out at me as being "profileable" (sp?!) – assessment data (assessment method, weighting, whether it was group work or not):
and contact times (that is, hours of contact and contact type):
I had some code kicking around for doing treemap views so I did a couple of quick demos [code]. First up, a view over the assessment strategy for core modules in a particular programme:
(I really need to make explicit the programme…)
Blocks are coloured according to level and sized according to product of points value for the course and assessment type weighting.
We can also zoom in:
I took the decision to use colour to represent level, but it would also be possible to pull the level out into the hierarchy used to configure the tree (for example having Level 1, Level 2, Level 3 groupings at the top?) I initially used the weighting to set the block size, but then tweaked it to show the product of the weighting and the number of credit points for the module, so for example a 60 point module with exam weighting 50% would have size 60*0.5 = 30, whereas a 15 point module with exam weighting 80% would have size 15*0.8 = 12.
Note that there are other ways we could present these hierarchies. For example, another view might structure the tree as: programme – level – module – assessment type. Different arrangements can tell different stories, be differently meaningful to different audiences, and be useable in different ways… Part of the art comes from picking the view that is most appropriate for addressing a particular problem, question or intention.
Here's an example of view over the contact hours associated with core modules in the same programme:
(Note that I didn't make use of the group work attribute which should probably also be added in to the mix?).
Looking at different programmes, we can spot different sorts of profile. Note that there is a lot wrong with these visualisations, but I think they do act as a starting point for helping us think about what sorts of view we might be able to start pulling out of the data now it's available. For example, how are programmes balanced in terms of assessment or contact over their core modules? One thing developing the above charts got me thinking about was how to step up a level to allow comparison of core module assessment and contact profiles across programmes leading to a particular qualification, or across schools? (I suspect a treemap is not the answer!)
It's also worth noting that different sorts of view might be appropriate for different sorts of "customer": potential student choosing a programme, student on a programme, programme manager, programme quality committee, and so on.
And it's also worth noting that different visualisation types might give a more informative view over the same data structure. On my to do list is to have a play with viewing the data used above in some sort of circular enclosure diagram (or whatever that chart type is called!) for example. (See the next post in this series, which amongst other things made me realise how partial/fragmentary the data displayed in the above treemaps actually is…)
Having had a play, a couple more observations came to mind about the API. Firstly, it could be useful to annotate modules with a numerical (integer) attribute relating to a standardised educational level, such as the FHEQ levels. (At the moment, modules are given level descriptors along the lines of "Level 3", relating to a third year course, akin to FHEQ level 6). Secondly, relating to assessment, it might be useful (down the line) to know how the grade achieved in a module at a particular level contributes to the final grade achieved at the end of the programme.
Playing with the data, I also found a little bug: in resources of the form https://n2.online.lincoln.ac.uk/module_links/id/273, the nuclues_url is incorrectly given as https://n2.online.lincoln.ac.uk/module_link/id/273 (i.e. the incorrect path element module_link which should be module_links).
Getting ONCourse With Course Data
In a post a couple of weeks ago – COuRsE Data – I highlighted several example questions that might usefully be asked of course data, thinks like "which modules are associated with any particular qualification?" or "which modules deliver which qualification level learning outcomes?".
As the University of Lincoln ONCourse project comes to an end [disclosure: I am contracted on the project to do some evaluation], I thought it might be interesting to explore the API that's been produced to see just what sorts of question we might be able to ask, out of the can.
Note that I don't have privileged access to the database (though I could possibly request read access, or maybe even a copy of the database, or at least its schema), but that's not how I tend to work. I play with things that are in principle publicly available, ideally things via openly published URLs and without authentication (no VPN); using URL parameter keys is about as locked down as I can usually cope with;-)
So what's available? A quick skim of the Objects returned via the API turns up some potentially interesting sounding ones in a course data context, such as: Accrediting Body, Assessment, Contact Type and Time, Course Code, Delivery Mode, Learning Outcome, Module Code, Programme Outcome.
So let's just pick one and see how far we can get… We can start at the bottom maybe, which is presumably Module.
A call to the API on /modules returns listings of the form:
{ id: 97, nucleus_url: "https://n2.online.lincoln.ac.uk/modules/id/97", module_code: { id: 28, nucleus_url: "https://n2.online.lincoln.ac.uk/module_codes/id/28", code: "FRS2002M" }, title: "Advanced Crime Scene Investigation and Analysis 2012-13", level: { id: 2, nucleus_url: "https://n2.online.lincoln.ac.uk/levels/id/2", description: "Level 2" } }
Looking at the record for an actual module gives us a wealth of data, including: the module code, level and number of credit points; a synopsis and marketing synopsis; an outline syllabus (unstructured text, which could cause layout problems?); the learning and teaching strategy and assessment strategy; a set of module links to programmes the module is associated with, along with core programme data; a breakdown of contact time and assessments; and prerequisites, co-requisites and excluded combinations.
There does appear to be some redundancy in the data provided for a module, though this is not necessarily a bad thing in pragmatic terms (it can make like convenient). For example, the top level of a modules/id record looks like this:
and lower down the record, in the /assessments element we get duplication of the data:
As something of a tinkerer, this sort of thing works for me – I can grab the /assessments object out of a modules/id result and pass it around with the corresponding module data neatly bundled up too. But a puritan might take issue with the repetition…
Out of the box then, I can already start to write queries on a module if I have the module ID. I'll give some code snippets of example Python routines as I play my way through the API…
import urllib2, json def gurl(url): return json.load(urllib2.urlopen(url)) def jgrabber(u): root='https://n2.online.lincoln.ac.uk' return gurl(root+u) #Note that API calls are actually signed with a key (not show in URLs) def dd(): print "-----" #Can I look up the programmes associated with a module given its ID? def grabModulesId(id): return jgrabber( '/modules/id/'+str(id) )['result'] def printProgsFromModuleID(moduleID,d=''): if d=='': d=grabModulesId(moduleID) dd() print 'Module:', d['title'], '(', d['module_code']['code'], d['level']['description'], ',', d['credit_rating'], 'points)' dd() for r in d['module_links']: print 'Programme:', r['programme']['programme_title'] print 'Course:', r['programme']['course_title'], "(",r['programme']['course_code']['code'],")" dd() '''Example result: >>> printProgsFromModuleID(97) ----- Module: Advanced Crime Scene Investigation and Analysis 2012-13 ( FRS2002M Level 2 , 30 points) ----- Programme: Forensic Science Course: Forensic Science Bachelor of Science with Honours (BSc (Hons)) 2011-12 ( FRSFRSUB ) ----- Programme: Criminology and Forensic Invesitgation Course: Criminology and Forensic Invesitgation Bachelor of Science with Honours (BSc (Hons)) 2011-12 ( CRIFRSUB ) '''
The /module_codes call then allows us to see when this module was presented:
#When was a module presented? def grabModuleCodesId(id): return jgrabber( '/module_codes/id/'+str(id) )['result'] def printPresentationsFromModuleCode(moduleCode,d=''): if d=='': d=grabModuleCodesId(moduleCode) dd() print 'Presentations of',d['code'] dd() for r in d['modules']: print r['title'] dd() '''Example result: >>> printPresentationsFromModuleCode(28) ----- Presentations of FRS2002M ----- Advanced Crime Scene Investigation and Analysis 2010-11 Advanced Crime Scene Investigation and Analysis 2011-12 Advanced Crime Scene Investigation and Analysis 2012-13 Advanced Crime Scene Investigation and Analysis 2013-14 ----- '''
We can also tweak the first query to build a bigger report. For example:
#Combination effect def getModuleCodeFromModuleID(moduleID,d=''): if d=='':d=grabModulesId(moduleID) return d['module_code']['id'] moduleID=97 d=grabModulesId(moduleID) printProgsFromModuleID(moduleID,d) moduleCode = getModuleCodeFromModuleID(moduleID,d) printPresentationsFromModuleCode(moduleCode)
One thing I'm not sure about is the way in to a moduleID in the first instance? For example, I'd like to be able to straightforwardly be able to get the IDs for any upcoming presentations of FRS2002M in the current academic year?
So what else might we be able to do around a module? How about check out its learning outcomes? My first thought was the learning outcomes might be available from the /modules data (i.e. actual module presentations), but they don't seem to be there. Next thought was to look for them in the abstracted module definition (from the module_codes), but again: no. Hmmm… Assessments are associated with a module, so maybe that's where the learning outcomes come in (as subservient to assessment rather than a module?)
The assessment record in the module data looks like this:
And if we click to to an assessment record we get something like this, which does include Learning Outcomes:
Philosophically, I'm not sure about this? I know that assessment is supposed to be tied back to LOs, and quality assurance around a course and its assessment is typically a driver for the use of LOs. But if we can only find the learning outcomes associated with a module via its assessment..? Hmmm… Data modeling is often fraught with philosophical problems, and I think is is one such case?
Anyway, how might we report on the learning outcomes associated with a particular module presentation? Here's one possible way:
#Look up assessments def assessmentByModuleID(moduleID,d=''): if d=='':d=grabModulesId(moduleID) return d['assessments'] #Look up learning outcomes def learningOutcomesByModuleID(moduleID,d=''): if d=='': d=assessmentByModuleID(moduleID) dd() for r in d: assessment=gurl(r['nucleus_url'])['result'] print assessment['module']['title'], '(', assessment['module']['module_code']['code'], ')', assessment['assessment_method'],'Learning Outcomes:' learningOutcomes=assessment['learning_outcomes'] for learningOutcome in learningOutcomes: print '\t- ',learningOutcome['description'] dd() #Example call learningOutcomesByModuleID(97) '''Example output Advanced Crime Scene Investigation and Analysis 2012-13 ( FRS2002M ) Exam Learning Outcomes: - Identify factors which affect persistence and transfer of trace evidence materials and demonstrate practical skills in recovery and physical and chemical analysis of trace evidence using a variety of specialised techniques - Discriminate different types of hairs and fibres on the basis of morphology and optical (e.g. birefringence) and chemical properties (e.g. dye composition) ... '''
We can also query the API to get a list of learning outcomes directly, and this turns up a list of assessments as well as the single (?) module associated with the learning outcome. Does this mean that a particular learning outcome can't be associated with two modules? I'm not sure that's right? Presumably, database access would allow us to query learning outcomes by moduleID?
Okay – that's probably enough for now. The API seems to be easy enough to use, and I guess it wouldn't be too hard to come up with some Google Spreadsheet formulae to demonstrate how they could be used to pull the course data into that sort of workspace (eg along the lines of Using Data From Linked Data Datastores the Easy Way (i.e. in a spreadsheet, via a formula)).
In the next post, I'll a peak at some of the subject keywords, and maybe have a play at walking through the data in order to generate some graphs (eg maybe along the lines of what Jamie has tried out previously: In Search of Similar Courses). There;s also programme level outcomes, so it might be interesting trying do do some sort of comparison between those and the learning outcomes associated with assessment in modules on a programme. And all this, of course, without (too much) privileged access…
PS Sod's Law from Lincoln's side means that even though I only touched a fragment of the data, I turned up some errors. So for example, in the documentation on bitbucket the award.md "limit" var was class as a "bool" rather than an "int" (which suggests a careful eye maybe needs casting over all the documentation. Or is that supposed to be my job?! Erm…;-) In programme/id=961 there are a couple of typos: programme_title: "Criminology and Forensic Invesitgation", course_title: "Criminology and Forensic Invesitgation Bachelor of Science with Honours (BSc (Hons)) 2011-12". Doing a bit of text mining on the data and pulling out unique words can help spot some typos, though in the above case Invesitgation would appear at least twice. Hmmm…
Looking at some of the API calls, it would be generally useful to have something along the lines of offset=N to skip the first N results, as well as returning "total-Results=" in the response. Some APIs provide helper data along the lines of "next:" where eg next=offset+num_results that can be plugged in as the offset in the next call if you want to roll your own paging. (This may be in the API, but I didn't spot it?). When scripting this, care just needs be taken to check that a fence post error doesn't sneak in.
Okay – enough for now. Time to go and play in the snow before it all melts…
COuRsE Data
One of the things that has never really been clear to me is what it is that universities think they sell and what students think they are "buying". (OU modules have always(?) had a price tag associated with them, although large amounts of financial support has also traditionally been available). One partial view might focus on one of the more tangible exchanges that are evident when taking a university degree, specifically the modules taken as part of a qualification programme, and the way they are bundled, organised and presented to students. Curriculum innovation works at both the level of keeping these modules up to date, as well as introducing new modules (and potentially new degree programmes, either as new aggregations of, and pathways through, collection of modules).
If we think of universities as organisations in the business of selling, at least in part, structured collections of course modules*, then we might speculate around the processes that are used to come up with new collections that are desirable to fee-paying students (and consequently, employers).
(* I know, I know – we might also think of the cost centre services that go along with course delivery as part of the package, the assessment, the facilities, the pastoral care, the structured academic content; or the "payoff" in terms of improved employability, or higher lifetime earnings. But when I buy a bar of chocolate, I don't see it as covering the factory automation, raw ingredients, logistics or supply chain costs, nor am I buying in to delight or gluttony. I'm buying a bar of chocolate. I'm also not saying that the courses are necessarily the thing students are buying, it's just one particular lens we can use to see whether it makes storytelling sense to view the system in that way…)
In part, programmes of study leading to named qualifications in particular subject or topic areas are influenced by the QAA benchmark statements:
Subject benchmark statements set out expectations about standards of degrees in a range of subject areas.
Subject benchmark statements do not represent a national curriculum in a subject area. Rather, they allow for flexibility and innovation in programme design within an overall conceptual framework established by an academic subject community. They are intended to assist those involved in programme design, delivery and review and may also be of interest to prospective students and employers, seeking information about the nature and standards of awards in a subject area.
In terms of curriculum development, there is a chicken-and-egg element to the role QAA statements can play. As the Recognition scheme for subject benchmark statements suggests in its guidance relating to the creation of new benchmark statements:
The proposal will need to demonstrate that a new or revised statement would provide the
benefits of a wider understanding about the scope and nature of the subject and the academic
standards underpinning it. This could be desirable for one or more of the following reasons.
• The subject is growing and more degree programmes are being provided in it
• A degree in the subject may be required for entry into a profession, but there are no explicit
academic standards associated with the subject for this purpose. There may also be a lack of
understanding within the relevant profession of what level of attainment can be expected
of a graduate in the subject, or of its appropriateness for entry into the profession
• The prospective benefits of agreed and explicit standards in the relevant subject have been
highlighted by, for example, external examiners and validating boards, higher education
providers, subject groups, or stakeholder organisations.
(See also Statements in development for examples of statements currently under consideration.)
Unpicking the course module view a little further, modules are typically associated with notional academic credit points, which are awarded "when you have shown, through assessment, that you have successfully completed a module or a programme by meeting the specific set of learning outcomes for that module or programme" (Academic credit in higher education in England – an introduction; see also QAA – Academic Credit). Note that credit points do not reflect how well you passed the assessment, just that you achieved at least the minimum standard required. Credit points themselves relate to two considerations: "[t]he credit value indicates both the amount of learning expected (the number of credits) and its depth, complexity and intellectual demand (the credit level)." The "amount of learning" is captured by the "notional hours of
learning" spent on the subject within the module. The level is based on level descriptors that "are used to help work out the level of learning in individual modules."
Credit level descriptors are guides that help identify the relative demand, complexity and depth of learning, and learner autonomy expected at each level, and also indicate the differences between the levels.
They are general descriptions of the learning involved at a particular level; they are not specific requirements of what must be covered in a particular module, unit or programme.
So to recap – modules are designed in order to deliver a set of learning outcomes (that include subject or topic specific learning outcomes as well as more general skills) that can be acquired in a notional amount of time and that are assessed at a particular academic level in exchange for a academic credit.
Qualifications are then awarded based on credit awarded in programmes of study, such as undergraduate or postgraduate degrees. Qualifications typically require the demonstration of some sort of progression through credit levels within a subject area, specify a range of qualification level learning outcomes that need to be delivered within the context of the programme as a whole, and may also require students to demonstrate aptitude across a range of assessment styles (or alternatively, offer a range of assessment styles so as not to disadvantage students who struggle with a particular style of assessment).
Whilst "traditional" universities typically offered named degree programmes in specific areas, the Open University originally offered an Open Degree (which is still available), in which students were free to choose whatever modules (then referred to as OU courses) they wanted, subject to certain requirements on the number of courses taken at each credit level (akin to each year of a traditional university degree; for more on credit points and credit equivalence. Whilst course choice was free, many students followed the same common pathways through courses to come out with degrees that were, essentially subject degrees. In recent years, the OU has moved increasingly towards the award of named degrees, where students are required to take particular modules. Indeed, it is increasingly difficult to find the individual modules that students originally "bought" on the OU website – the emphasis now is on selling qualification level credit bundles, rather than module level credit points.
But how do universities decide what modules to offer? And how does curriculum innovation work? A bottom-up approach might be to refresh modules within a qualification, and then create new qualifications by rebundling sets of modules that together define some sort of coherent whole (this is how 'as-if' subject degrees were self-assembled by OU students in the Open Degree). A top-down approach might be to come up with an idea for a degree programme, and then commission modules to deliver that programme of study. Alternatively, we might look to mass-dynamics in a free choice system, such as an open degree, and come up with a middle-out(?) approach that suggests programmes of study that formalise the module collections freely chosen by students interested in studying a particular set of topics that make sense to them.
(It is interesting to note that possibly uniquely within UK Higher Education, The Open University had the scale of numbers in undergraduate students to start to say interesting things about the way students selected courses under the Open degree model. Furthermore, as popularity in "Big Data" solutions and recommendations driven by crowd-behaviour becomes commonplace, so the OU is reducing the amount of personalisation possible by pushing hard-coded, predefined pathways. At the same time, institutions such as Southampton University seem to be looking to open up personalisation pathways (for example, Southampton Curriculum innovation, discussed here: Graduates for the 21st Century – Curriculum innovation [audio]) and standalone HE level courses are increasingly available, sans credit, (as marketing warez; but for what exactly?) via the various open online course platforms.
So now we're at the point where I actually wanted to start this post… How do we go about the process of curriculum innovation (for example, OECD Education Working Papers No. 82 – Bringing About Curriculum Innovations) given that we already have a load of inventory? If we sell credit points in particular subject areas or topics, how do we decide what topics to cover and how do we bundle those points up into qualifications?
One place to start might be mapping out where we are at the current time, which is where course data comes in. For example, what does the interest map based on learning outcomes delivered by your university actually look like? Or if you work in HE, do you know (or can you readily find out):
- which modules are associated with any particular qualification?
- which qualifications are associated with any particular module, either as a required or optional component?
- which modules have path dependencies (eg where one module is the pre-requisite of another, or modules are excluded combinations)?
- which module are required in which pathways, and which are optional?
- in free choice modules (that maybe span programmes), which modules tend to be taken together?
- which modules deliver which qualification level learning outcomes?
- which modules deliver which sort of assessment types?
- are there any modules that already offer particular learning outcomes at a particular level?
To provide a little more context, imagine these scenarios:
- Module X is tired and needs to be replaced – what qualifications or other modules might be affected as a result? For example, does the module uniquely cover a a particular qualification level learning outcome, or assessment type?
- A new qualification is proposed with a particular set of learning outcomes – what modules are available that already deliver some (or all) of these learning outcomes?
- The quality folk want to know how your programme demonstrates progression across credit levels with respect to a particular set of subject related learning outcomes. Can you easily map this out?
- The quality folk also want to know whether a particular course is gameable in terms of assessment types covered by the course modules. Could a student select a set of modules that means they never have to do teamwork, project work/report, a presentation, an exam, etc?
- You need to generate a set of course transcripts (sets of learning outcomes, by credit level) for a proposed new assemblage of outstanding modules, some of which are core/compulsory modules, some of which are optional. Can you do it?
- Do you have the scaffolding data available to build course recommenders based on population flows and module selections of previous cohorts of student?
- Which modules deliver the content that potential students think they want to study, eg when searching your online course prospectus (you do use search logs for situational awareness around what potential students are searching for, don't you?!)
So – how well do you fare?
[Note: this post is inspired by personal reflections around the University of Lincoln ON Course Course data project, on which I have, via the OU, a small consultancy retainer, and of which: more later.]
– Scraperwiki Powered OpenLearn Searches – Learning Outcomes and Glossary Items
– Generating OpenLearn Navigation Mindmaps Automagically


text:
BRISTOL, Tenn. – Mason Casner and Eddie Moushikhian led the Tornado offensively with six kills each in the team's three-set win over the Rust College Bearcats on Friday night. King earned their first win of the season to even their overall record at 1-1 leading into Saturday morning's doubleheader at the Student Center Complex.
Junior Stephen Brown (Lawrenceville, Ga.) led the Tornado's breakaway in the first set that included a pair of services aces from the line. Brown took the Tornado from a one-point lead to a five-point advantage, 13-8, before turning the ball back over the Bearcats. King's lead never dipped below four points for the duration of the set after freshman Eddie Moushikhian (Alpharetta, Ga.) recorded a kill that sparked his own rally from the service line to build a seven-point lead. Rust committed eight attack errors down the stretch to help King to a 25-15 opening set victory. Freshman Matthew Lychock (Las Vegas, Nev.) and senior Michael Koebel (Richmond, Va.) paired up for two big blocks at the net to aid in taking the opening frame.
King (1-1) ran out to a 9-3 run early in the second set and kept the momentum going as Rust's hitting woes continued. Brown added two more services aces from the line to help build a nine-point lead, 17-8, at one point. Rust committed 10 attack errors before Brown sealed the second set with his third kill of the frame. With the 25-19 win, the Tornado took a two-set lead in the match before running away with the third.
Mason Casner (Culpepper, Va.) came off of the bench and recorded five kills to pace the Tornado in their 25-13 victory in the third set. King hit at a .476 success rate as a team and had three players hit .500 or better in the final frame. After recording three kills in the first set, Moushikhian put together three more in the third on four tries (.750).
Edward Peter led the Bearcats with five kills while Gino Pierre and Shamal James both had four. Razeem Huggins led the team with 3.5 total blocks, including three solo.
Junior Jeff Bosslett (St. Louis, Mo.) had 13 assists for the Tornado after entering the game for injured setter Ashton Hippenstiel.
Mason Casner led the team in hitting percentage, finishing the night .857 while Moushikhian hit .556 (6-of-9, 1 error). Stephen Brown closed in with five kills and led the team with five digs.
The Tornado dominated the net with 7.0 team blocks behind 12 block assists and a solo block. Five players had two block assists, each.
The Tornado have a quick turnaround when they begin a doubleheader tomorrow morning at 10 a.m. in the Student Center. King will host newcomer to Conference Carolinas Men's Volleyball Belmont Abbey and close the day out with Division I Quincy University.