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Big Data and Assessment for Learning in Nigerian Universities: Prospects and Challenges

This study explored the perceptions of university teachers on sources of big data for assessment, and evaluated the prospects and challenges of using big data in assessment for learning in Nigerian universities. A mixed method approach was adopted for collecting data from a random sample of 134 university teachers in Nigeria. A 30-item Big Data Assessment for Learning Scale (B_DALS) and a semi-structured interview schedule were used for data collection. Quantitative data collected was analysed using descriptive statistical techniques, while themes in the qualitative data were identified and used to corroborate the quantitative data. The findings reveal that less than 50% of the teachers were able to identify different sources of big data that can be used in assessment for learning. The teachers perceived positively, the possibility of using big data for improving teaching and learning (3.88±0.98), reducing students’ attrition (3.87±0.98), planning teaching and learning activities (3.58±1.01), among others. It was also found that major challenges of using big data in assessment for learning are; how to put rich data into usable form to support learning (3.57±1.03), capacity to maintain learning analytics system and design effective intervention (3.62±1.05), and aligning educational data with pedagogically-based action (3.64±0.95). It was concluded that big data should be used in assessment for learning to reduce high rate of withdrawal and probation placement of students in Nigerian universities.

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