Learning Analytics for Teacher’s Dashboard in a Course Result System
Perustieteiden korkeakoulu | Master's thesis
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Master’s Programme in Computer, Communication and Information Sciences
AbstractWith the digital transformation of learning and the spread of online learning under the impact of COVID-19, huge amounts of learning data are being generated. How to utilize and analyze this learning data has led to a new field -- Learning Analytics (LA). LA demonstrates the collection, use and analysis of data generated by students in the learning process to predict student behavior and provide feedback. The goal of this thesis is to redesign a course result system (OSR) with LA functions. OSR is a results registration system used by the Department of Computer Science at Aalto University for over a decade. The development technology used by OSR is outdated and does not have the satisfying LA features for teachers. Meanwhile, this thesis tries to build a prototype of the new system based on the cloud platform (Salesforce). The research questions are: what is the state of art of the old system, what LA functions the new system needs, and what are the requirements of the new system. In order to answer these three research questions, this thesis first conducts a literature review. This thesis reviews the literature on OSR, A+, LA, cloud service models, and Salesforce. Through literature review and practical experience of OSR, this thesis obtains the state of art of the existing system as well as possible functional requirements and LA requirements. This thesis uses the constructive research method to design the new system. To gather functional needs and LA requirements from users, this thesis performed semi-structured interviews with teachers. After analyzing and summarizing the interview results, this thesis concludes the user needs. After comparing, merging and screening the requirements from the OSR and LA reviews in the Literature Review chapter, the requirements of the new system are summarized in this thesis. As for final requirements, the following three findings are made in this thesis. First of all, teachers are satisfied with the final grade calculation function and database function provided by the old system. The new system can follow the design of final grade calculation function of the old system. Second, although teachers were satisfied with most of the features of the old system, they spent a lot of time verifying the results. This suggests that they need a more reassuring system. Third, the old system provided only some statistical functions, and few teachers used them. Teachers hope the new system will provide them with more LA features, such as producing periodic reports for them to monitor students' progress in real time.
Thesis advisorLehtinen, Teemu
learning analytics, course result system, user requirement, salesforce