Assessment and feedback processes shape students behaviour, learning and skill development. Computer-aided assessments are increasingly being used to support problem-solving, marking and feedback activities. However, many computer-aided assessment environments only replicate traditional pencil-and-paper tasks. Attention is on grading and providing feedback on the final product of assessment tasks rather than the processes of problem solving. Focusing on steps and problem-solving processes can help teachers to diagnose strengths and weaknesses, discover problem-solving strategies, and to provide appropriate feedback to students. This thesis presents a semi-automatic framework for capturing and marking students solution steps in the context of elementary school mathematics. The first focus is on providing an interactive touch-based tool called MuTAT to facilitate interactive problem solving for students. The second focus is on providing a marking tool named Marking Assistant which utilises the case-based reasoning artificial intelligence methodology to carry out marking and feedback activities more efficiently and consistently. Results from studies carried out with students showed that the MuTAT prototype tool was usable, and performance scores on it were comparable to those obtained when paper-and-pencil was used. More importantly, the MuTAT provided more explicit information on the problem-solving process, showing the students thinking. The captured data allowed for the detection of arithmetic strategies used by the students. Exploratory studies conducted using the Marking Assistant prototype showed that 26% savings in marking time can be achieved compared to traditional paper-and-pencil marking and feedback. The broad feedback capabilities the research tools provided can enable teachers to evaluate whether intended learning outcomes are being achieved and so decide on required pedagogical interventions. The implications of these results are that innovative CAA environments can enable more direct and engaging assessments which can reduce staff workloads while improving the quality of assessment and feedback for students.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:706207 |
| Date | January 2016 |
| Creators | Adesina, Adewale O. |
| Publisher | Loughborough University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://dspace.lboro.ac.uk/2134/23342 |
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