Literaturnachweis - Detailanzeige
Autor/inn/en | Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi |
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Titel | Automatically Detecting Previous Programming Knowledge from Novice Programmer Code Compilation History |
Quelle | In: Informatics in Education, 22 (2023) 2, S.277-294 (18 Seiten)Infoseite zur Zeitschrift
PDF als Volltext |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 1648-5831 |
Schlagwörter | Prior Learning; Programming; Computer Science Education; Markov Processes; Likert Scales; Introductory Courses; Novices; Algorithms; Student Behavior; Teaching Methods; Learning Processes; Programming Languages; Undergraduate Students; Artificial Intelligence; Foreign Countries; Finland Vorkenntnisse; Programmierung; Computer science lessons; Informatikunterricht; Markowscher Prozess; Likert-Skala; Einführungskurs; Algorithm; Algorithmus; Student behaviour; Schülerverhalten; Teaching method; Lehrmethode; Unterrichtsmethode; Learning process; Lernprozess; Künstliche Intelligenz; Ausland; Finnland |
Abstract | Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student programming behavior can be modeled as a Markov process. The resulting transition matrix can then be used in machine learning algorithms to create clusters of similarly behaving students. We describe in detail the state machine used in the Markov process and how to compute the transition matrix. We compute the transition matrix for 665 students and cluster them using the k-means clustering algorithm. We choose the number of cluster to be three based on analysis of the dataset. We show that the created clusters have statistically different means for student prior knowledge in programming, when measured on a Likert scale of 1-5. (As Provided). |
Anmerkungen | Vilnius University Institute of Mathematics and Informatics, Lithuanian Academy of Sciences. Akademjos str. 4, Vilnius LT 08663 Lithuania. Tel: +37-5-21-09300; Fax: +37-5-27-29209; e-mail: info@mii.vu.lt; Web site: https://infedu.vu.lt/journal/INFEDU |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2024/1/01 |