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- Glassey, Richard, et al.
(författare)
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Learnersourcing analytics
- 2023
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Ingår i: Practicable Learning Analytics. - Cham : Springer International Publishing. ; , s. 155-175
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- A good source of data for learning analytics is the online questions and answers posed to the learners during the course. However, there are several reports on the challenges of question construction as these questions are time consuming to construct and verify, especially if you go beyond multiple-choice questions. One remedy to this is learnersourcing that includes the learners in the generation and verification of these questions for both pedagogical reasons and resource conservation. Learnersourcing is one solution to producing and improving learning activities at scale by leveraging student effort. It also creates a new layer of learner data to analyse: first, in terms of the behaviour traces from producing learning activities; and second in terms of the impressions that other learners and teachers have from taking or reviewing those activities. This chapter will introduce basic concepts and examples of learnersourcing along with examples and approaches to applying a learning analytics lens upon the data traces that are produced.
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| 2. |
- Östlund, Linus, et al.
(författare)
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It's Never too Early to Learn about Code Quality : A Longitudinal Study of Code Quality in First-year Computer Science Students
- 2023
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Ingår i: SIGCSE 2023. - New York, NY, USA : Association for Computing Machinery (ACM). ; , s. 792-798
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Konferensbidrag (refereegranskat)abstract
- Low code quality incurs a significant cost upon the software industry. Despite this, little serious effort has been devoted to the topic at the most basic levels of computing science education. Where studies have been conducted, the results are disappointing in terms of code quality. In this work, four iterations of a medium to large CS1 and CS2 course (n=200 students) were analyzed through the lens of code violations to better understand (1) what code violations occur most frequently, (2) how does their occurrence vary throughout the course, and (3) to what extent do teaching assistants have an effect upon code quality. Results showed a statistically significant improvement in code quality over 19 assignments in all four course iterations. In particular, when a single violation was the focus of a learning outcome, the effects were both a dramatic fall and sustained low occurrence. However, this improvement was mostly focused on the three most frequently occurring violations (> 70%), which masked an increase in lesser occurring violations throughout the course. Finally, the effects from different teaching assistants were found to be random at best, contradicting expectations that their influence would be easily detected. Given that explicit learning outcomes targeted at code quality had an effect and teaching assistant influence had no effect, a path forward to improving code quality might combine these forces without creating too many additional demands upon the already stretched teaching resources with CS1 and CS2 courses.
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