{'fraction_non_alphanumeric': 0.02572347266881029, 'fraction_numerical': 0.0019292604501607716, 'mean_word_length': 5.0310077519379846, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Predicting Education System Outcomes: A Scientific Approach 1

Many people want to improve education. So do we. Many researchers argue that such change must be systemic, since attempts at piecemeal change have made little difference in our current education systems, which still operate largely as they have in the past. The major question is: What should we change in the current education system, and how do we know it will work? We argue that what we need is a good systems theory for predicting outcomes of such changes. Otherwise, we may be making changes that, while well-intended, may not result in desired outcomes—possibly even making things worse, rather than better. In this paper we provide an overview of a change strategy that is inquiry-based and which relies on a scientific systems theory (ATIS). This is followed by a simple example of how this theory can be applied to a fictional school system. After discussing the foundations of Axiomatic Theories of Intentional Systems (ATIS) and examples of systems properties, we describe computer software programs now under development that allow people to apply this theory, to make predictions, and to measure change: 1) PESO: Predicting Education System Outcomes, and 2) APT&C: Analysis of Patterns in Time and Configuration. APT&C provides an alternative measurement and analysis paradigm for investigating dynamic and structural relations in systems. Finally, we discuss work remaining to be done on this long-term research and development project before it can be implemented in practice.