| 1. |
- Lister, Raymond, et al.
(författare)
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Differing Ways that Computing Academics Understand Teaching.
- 2007
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Ingår i: Australian Computer Science Communications. - 0157-3055. ; 29:5, s. 97-106
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents first results from a wide-ranging phenomenographic study of computing academics' understanding of teaching. These first results focus upon four areas: the role of lab practical sessions, the experience of teaching success, conceptions of motivating and engaging students, and the granularity of the teacher's focus. The findings are comparable with prior work on the understandings of academics in other disciplines. This study was started as part of a workshop on phenomenography. Most participants at the workshop received their first training in phenomenography. This paper summarises the structure of the workshop.
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| 2. |
- Cassel, Lillian, et al.
(författare)
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Four relections on the history of ITiCSE
- 2018
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Ingår i: ACM inroads. - : ACM Digital Library. - 2153-2184 .- 2153-2192. ; 9:4, s. 40-46
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Tidskriftsartikel (refereegranskat)abstract
- In 1996, recognizing a growing worldwide interest in community education, SIGCSE started a new conference in Europe—now known as the Innovation and Technology in Computer Science Education conference (ITiCSE). Following the success of the first ITiCSE, it has been held annually, typically in Europe, ever since. ITiCSE has developed its own special character, providing unique and valuable experiences for participants. In this article we reflect upon ITiCSE, its establishment and development into a leading venue for computing education researchers and practitioners.
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| 3. |
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| 4. |
- Ihantola, Petri, et al.
(författare)
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Educational Data Mining and Learning Analytics in Programming : Literature Review and Case Studies
- 2016
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Ingår i: Proceedings of the 2015 ITiCSE on Working Group Reports. - New York, NY, USA : ACM Digital Library. - 9781450341462 ; , s. 41-63
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Konferensbidrag (refereegranskat)abstract
- Educational data mining and learning analytics promise better understanding of student behavior and knowledge, as well as new information on the tacit factors that contribute to student actions. This knowledge can be used to inform decisions related to course and tool design and pedagogy, and to further engage students and guide those at risk of failure. This working group report provides an overview of the body of knowledge regarding the use of educational data mining and learning analytics focused on the teaching and learning of programming. In a literature survey on mining students' programming processes for 2005-2015, we observe a significant increase in work related to the field. However, the majority of the studies focus on simplistic metric analysis and are conducted within a single institution and a single course. This indicates the existence of further avenues of research and a critical need for validation and replication to better understand the various contributing factors and the reasons why certain results occur. We introduce a novel taxonomy to analyse replicating studies and discuss the importance of replicating and reproducing previous work. We describe what is the state of the art in collecting and sharing programming data. To better understand the challenges involved in replicating or reproducing existing studies, we report our experiences from three case studies using programming data. Finally, we present a discussion of future directions for the education and research community.
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| 5. |
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| 6. |
- Sanders, Kate, et al.
(författare)
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How Statistics Are Used in Computing Education Research
- 2018
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Ingår i: ITiCSE 2018. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450357074 ; , s. 381-381
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Konferensbidrag (refereegranskat)abstract
- Conferences such as ITiCSE have recently seen an increase in the number of papers presenting empirical research in computing education. While empirical research need not be quantitative, there has been a corresponding increase in the number of papers that present some level of statistical analysis to support their arguments. This poster introduces a project that is exploring how - and how well statistics are used and reported in computing education research.
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| 7. |
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| 8. |
- Sheard, Judy, et al.
(författare)
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MOOCs and their impact on academics
- 2014
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Ingår i: Proc. 14th International Conference on Computing Education Research. - New York : ACM Press. - 9781450330657 ; , s. 137-145
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Konferensbidrag (refereegranskat)
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