{'fraction_non_alphanumeric': 0.02545068928950159, 'fraction_numerical': 0.0010604453870625664, 'mean_word_length': 4.721212121212122, '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}}
Data-based decision making in teams: enablers and barriers

ABSTRACT Data use is becoming more important in higher education. In this case study, a team of teachers from a teacher education college was supported in data-based decision making by means of the data team procedure. This data team studied the reasons why students drop out. A team's success depends in part on whether the team is able to develop and apply new knowledge based on data. To investigate this, we focused on the depth of inquiry within the data team's conversations, because successful teams discuss data in depth. We observed the data team for 2 years, investigating factors that affected the depth of the conversations in the data team. The results show that depth was influenced by factors related to data and data systems (such as access to relevant data), individual factors (such as belief in data use), and organisational factors (guidance from the data coach).