Competence-based Assessment of Programming Assignments

被引:0
作者
Ploesch, Reinhold [1 ]
Groher, Iris [1 ]
Hofer, Alexander [1 ]
机构
[1] Johannes Kepler Univ Linz, Business Informat SE, Linz, Austria
来源
2024 36TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING EDUCATION AND TRAINING, CSEE & T 2024 | 2024年
关键词
competence; learning analytics; competence-based learning; automated assessment;
D O I
10.1109/CSEET62301.2024.10662988
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In recent years, computer science education has increasingly focused on the development and application of automated code assessment methods. Test-based assessments of student submissions generate large quantities of data that could be used for learning analytics. Existing literature highlights a predominant use of unit tests for grading rather than for extracting insights into students' challenges in learning programming concepts. Moreover, competence models, which systematically outline required learning outcomes, are increasingly important during curriculum design. We introduce a novel approach for systematically developing programming assignments aligned with competence models. This method also aids educators in creating unit tests that support competence-based learning analytics. As our method maps competences to individual test cases and thereby quantifies a student's proficiency in an assignment, this helps educators to evaluate, whether students have the ability to understand and master the required competences. Experimental application of our method demonstrated enhanced clarity in understanding student assignments and a considerable improvement in the quality of learning analytics data.
引用
收藏
页数:10
相关论文
共 17 条
  • [1] Anke, 2017, ICERI2017 P SEV SPAI, P658, DOI [10.21125/iceri.2017.0258, DOI 10.21125/ICERI.2017.0258]
  • [2] [Anonymous], 2009, A Formal Model of Competence-Based Assessment., P428
  • [3] [Anonymous], 2015, P 5 INT C LEARN AN K, P146, DOI [10.1145/2723576.2723589, DOI 10.1145/2723576.2723589]
  • [4] [Anonymous], 2019, ACM Inroads., V10, P30, DOI [10.1145/3324888, DOI 10.1145/3324888]
  • [5] Arnold K.E., 2012, P 2 INT C LEARN AN K, P267, DOI [DOI 10.1145/2330601.2330666, 10.1145/2330601.2330666doi.org/10.1145/2330601.2330666, DOI 10.1145/2330601.2330666DOI.ORG/10.1145/2330601.2330666]
  • [6] Bennedsen Jens, 2019, Failure rates in introductory programming.
  • [7] Evaluation of competence-based teaching in higher education: From theory to practice
    Bergsmann, Evelyn
    Schultes, Marie-Therese
    Winter, Petra
    Schober, Barbara
    Spiel, Christiane
    [J]. EVALUATION AND PROGRAM PLANNING, 2015, 52 : 1 - 9
  • [8] A Teacher-facing Learning Analytics Dashboard for Process-oriented Feedback in Online Learning
    Dourado, Raphael A.
    Rodrigues, Rodrigo Lins
    Ferreira, Nivan
    Mello, Rafael Ferreira
    Gomes, Alex Sandro
    Verbert, Katrien
    [J]. LAK21 CONFERENCE PROCEEDINGS: THE ELEVENTH INTERNATIONAL CONFERENCE ON LEARNING ANALYTICS & KNOWLEDGE, 2021, : 482 - 489
  • [9] Gandrass Niels, 2019, Gesellschaft f ur Informatik e.V.., DOI [10.18420/ABP2019-1, DOI 10.18420/ABP2019-1]
  • [10] Garmann Robert, 2016, Graja-Autobewerter f ur Java-Programme