Automatically Detecting Previous Programming Knowledge from Novice Programmer Code Compilation History

Autor/inn/en	Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi
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 kostenfreie Datei Verfügbarkeit
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 + Suchen Sie Ihr Suchwort? 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