Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2020 IEEE Global Engineering Education Conference, EDUCON 2020 |
| Editors | Alberto Cardoso, Gustavo R. Alves, Teresa Restivo |
| Pages | 329-338 |
| Number of pages | 10 |
| ISBN (electronic) | 9781728109305 |
| Publication status | Published - 2020 |
| Externally published | Yes |
Abstract
To overcome the shortage of computer specialists, there is an increased need for correspondent study and training offers, in particular for learning programming. The automated assessment of solutions to programming tasks could relieve teachers of time-consuming corrections and provide individual feedback even in online courses without any personal teacher. The e-assessment system JACK has been successfully applied for more than 12 years up to now, e.g., in a CS1 lecture. However, there are only few solid research results on competencies and competence models for object-oriented programming (OOP), which could be used as a foundation for high-quality feedback.In a joint research project of research groups at two universities, we aim to empirically define competencies for OOP using a mixed-methods approach. In a first step, we performed a qualitative content analysis of source code (sample solutions and students' solutions) and as a result identified a set of suitable competency components that forms the core of further investigations. Semi-structured interviews with learners will be used to identify difficulties and misconceptions of the learners and to adapt the set of competency components. Based on that we will use Item Response Theory (IRT) to develop an automatically evaluable test instrument for the implementation of abstract data types. We will further develop empirically founded and competency-based feedback that can be used in e-assessment systems and MOOCs.
Keywords
- Computer science education, Educational technology, Electronic learning, Object oriented programming
ASJC Scopus subject areas
- Decision Sciences(all)
- Information Systems and Management
- Social Sciences(all)
- Education
- Engineering(all)
- General Engineering
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Proceedings of the 2020 IEEE Global Engineering Education Conference, EDUCON 2020. ed. / Alberto Cardoso; Gustavo R. Alves; Teresa Restivo. 2020. p. 329-338 9125323.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Automated Measurement of Competencies and Generation of Feedback in Object-Oriented Programming Courses
AU - Krugel, Johannes Arno
AU - Hubwieser, Peter
AU - Goedicke, Michael
AU - Striewe, Michael
AU - Talbot, Mike
AU - Olbricht, Christoph
AU - Schypula, Melanie
AU - Zettler, Simon
N1 - Funding information: Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – 412374068
PY - 2020
Y1 - 2020
N2 - To overcome the shortage of computer specialists, there is an increased need for correspondent study and training offers, in particular for learning programming. The automated assessment of solutions to programming tasks could relieve teachers of time-consuming corrections and provide individual feedback even in online courses without any personal teacher. The e-assessment system JACK has been successfully applied for more than 12 years up to now, e.g., in a CS1 lecture. However, there are only few solid research results on competencies and competence models for object-oriented programming (OOP), which could be used as a foundation for high-quality feedback.In a joint research project of research groups at two universities, we aim to empirically define competencies for OOP using a mixed-methods approach. In a first step, we performed a qualitative content analysis of source code (sample solutions and students' solutions) and as a result identified a set of suitable competency components that forms the core of further investigations. Semi-structured interviews with learners will be used to identify difficulties and misconceptions of the learners and to adapt the set of competency components. Based on that we will use Item Response Theory (IRT) to develop an automatically evaluable test instrument for the implementation of abstract data types. We will further develop empirically founded and competency-based feedback that can be used in e-assessment systems and MOOCs.
AB - To overcome the shortage of computer specialists, there is an increased need for correspondent study and training offers, in particular for learning programming. The automated assessment of solutions to programming tasks could relieve teachers of time-consuming corrections and provide individual feedback even in online courses without any personal teacher. The e-assessment system JACK has been successfully applied for more than 12 years up to now, e.g., in a CS1 lecture. However, there are only few solid research results on competencies and competence models for object-oriented programming (OOP), which could be used as a foundation for high-quality feedback.In a joint research project of research groups at two universities, we aim to empirically define competencies for OOP using a mixed-methods approach. In a first step, we performed a qualitative content analysis of source code (sample solutions and students' solutions) and as a result identified a set of suitable competency components that forms the core of further investigations. Semi-structured interviews with learners will be used to identify difficulties and misconceptions of the learners and to adapt the set of competency components. Based on that we will use Item Response Theory (IRT) to develop an automatically evaluable test instrument for the implementation of abstract data types. We will further develop empirically founded and competency-based feedback that can be used in e-assessment systems and MOOCs.
KW - Computer science education
KW - Educational technology
KW - Electronic learning
KW - Object oriented programming
UR - http://www.scopus.com/inward/record.url?scp=85087920696&partnerID=8YFLogxK
U2 - 10.1109/educon45650.2020.9125323
DO - 10.1109/educon45650.2020.9125323
M3 - Conference contribution
SP - 329
EP - 338
BT - Proceedings of the 2020 IEEE Global Engineering Education Conference, EDUCON 2020
A2 - Cardoso, Alberto
A2 - Alves, Gustavo R.
A2 - Restivo, Teresa
ER -