Using machine-learning and visualisation to facilitate learner interpretation of source material     

Annika Wolff  Paul Mulholland  Zdenek Zdrahal 《Interactive Learning Environments》2013,21(6):771-788

This paper describes an approach for supporting inquiry learning from source materials, realised and tested through a tool-kit. The approach is optimised for tasks that require a student to make interpretations across sets of resources, where opinions and justifications may be hard to articulate. We adopt a dialogue-based approach to learning whereby the student creates an external representation to reflect their current understanding of the task. This in turn prompts immediate feedback, designed to help the learner to see patterns or irregularities in their current perspective. Through the on-going feedback, the student is encouraged to make incremental changes to achieve a coherent outcome. In this approach, learners are encouraged to generate meaningful responses for themselves, rather than relying on feedback which explicitly provides an answer. This is aimed at prompting deeper processing and understanding of source materials in the context of the given learning goal.  相似文献   

A large-scale implementation of predictive learning analytics in higher education: the teachers’ role and perspective     

Herodotou  Christothea  Rienties  Bart  Boroowa  Avinash  Zdrahal  Zdenek  Hlosta  Martin 《Educational technology research and development : ETR & D》2019,67(5):1273-1306

By collecting longitudinal learner and learning data from a range of resources, predictive learning analytics (PLA) are used to identify learners who may not complete a course, typically described as being at risk. Mixed effects are observed as to how teachers perceive, use, and interpret PLA data, necessitating further research in this direction. The aim of this study is to evaluate whether providing teachers in a distance learning higher education institution with PLA data predicts students’ performance and empowers teachers to identify and assist students at risk. Using principles of Technology Acceptance and Academic Resistance models, a university-wide, multi-methods study with 59 teachers, nine courses, and 1325 students revealed that teachers can positively affect students’ performance when engaged with PLA. Follow-up semi-structured interviews illuminated teachers’ actual uses of the predictive data and revealed its impact on teaching practices and intervention strategies to support students at risk.

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Empowering online teachers through predictive learning analytics     

Christothea Herodotou  Martin Hlosta  Avinash Boroowa  Bart Rienties  Zdenek Zdrahal  Chrysoula Mangafa 《British journal of educational technology : journal of the Council for Educational Technology》2019,50(6):3064-3079

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