Abstract:

Adaptive learning applies to a range of technologies that monitor student performance and engagement with learning materials, in conjunction with a VLE and tailors the environment experienced by each student according to those observations. Adaptive learning systems offer different content choices to learners based on formative/summative assessments, and student responses obtained during engagement. CogBooks uses machine learning to drive its active learning system and continually tailors delivery to the user based on real-time interaction. The data science underlying CogBooks is similar to algorithms used by Google and Amazon; however, instead of recommending purchases, the software predicts learning resources that are best to meet the learning objectives.

This pilot project implemented adaptive learning using the CogBooks software in the delivery of two 2nd year units in the BSc(hons) and FdSc chemistry courses at MMU. These units were chosen since they contain a large cohort of students from different backgrounds and have a significant theory component bridging between disciplines. The project was launched for the BSc(hons) course in January 2016 and the influence of the adaptive learning materials upon student behaviour, satisfaction and learning outcomes was evaluated, and feedback from the students was obtained from a student survey and focus group. This analysis highlighted the impact CogBooks had on these students, which informed a review of the content, with minor modifications made for the release of the FdSc course in May 2016. For both courses, the CogBooks content provided a means of ongoing formative assessment throughout the delivery and these topics were part of the summative assessment for the end of unit exams during May and August 2016.

The results from student feedback highlighted the positive impact of adaptive learning technology upon enhancing the student learning experience and satisfaction. Where 72% of students surveyed indicated that they found it easy to explore subject materials using CogBooks and encouragingly, 82% thought the system had directed them to useful content. In addition, 87% found that it had helped them obtain a deeper understanding and 86% would have liked to have CogBooks for other units they were studying. The average exam marks for these units showed an increase of between 25-3% during 2015/16 compared to the previous academic year. The CogBooks topics were assessed in two sections of the exam papers, which comprised of a series of short questions worth 4 marks or long questions worth 20 marks and students were required to answer three short questions and one long question. The highest marks were exhibited from the results of short questions for both the BSc and FdSc exam papers, which showed an increase of 25 and 15% respectively. The increase in marks recorded for the long questions was modest in comparison, showing increases of 3 and 6% amongst the full-time BSc and FdSc students respectively.

Fundamentally, student reaction has been very encouraging and the integration of adaptive learning in this way can lead to significant educational gains, which give rise to valuable outputs that enhance the learning experience. The project is ongoing with continued development of these online resources during the 2016/17 academic year.

Keywords:

Adaptive learning, CogBooks, technology-enhanced learning, e-learning, inclusive/personal teaching.