Effects of different types of guidance on students' motivation and learning in a remote laboratory in computer science
During online learning, it is essential to provide instructional guidance to support learning. However, guidance can be given in different forms and quantities. Thus, one important challenge is to provide the right amount and type of instructional guidance. The aim of the study is to investigate typ...
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Published in | Computer science education Vol. 33; no. 3; pp. 375 - 399 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Norwood
Routledge
03.07.2023
Taylor & Francis Ltd |
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Abstract | During online learning, it is essential to provide instructional guidance to support learning. However, guidance can be given in different forms and quantities. Thus, one important challenge is to provide the right amount and type of instructional guidance.
The aim of the study is to investigate types of guidance which are effective for students with heterogenous programming knowledge and skills solving programming tasks in a remote laboratory.
We carried out two studies with a single factor pre-post-design with guidance (basic/enhanced) as a between-subjects factor.
In study 1, we implemented enhanced guidance in the form of prompts in the introduction to the tasks. Whereas we found no differences in learning outcome or extraneous cognitive load, students in the enhanced guidance group reported less intrinsic motivation, and logfiles revealed a lower programming performance. In study 2, we implemented enhanced guidance in the form of adaptive just-in-time explanations for error streaks. Enhanced guidance led to a lower extraneous cognitive load, and this way increased learning outcome.
The type and timing of instructional guidance for students in computer science matters. More guidance is not better in each case. Instructional guidance should be tailored to students' needs. |
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AbstractList | Background and ContextDuring online learning, it is essential to provide instructional guidance to support learning. However, guidance can be given in different forms and quantities. Thus, one important challenge is to provide the right amount and type of instructional guidance.ObjectiveThe aim of the study is to investigate types of guidance which are effective for students with heterogenous programming knowledge and skills solving programming tasks in a remote laboratory.MethodWe carried out two studies with a single factor pre-post-design with guidance (basic/enhanced) as a between-subjects factor.FindingsIn study 1, we implemented enhanced guidance in the form of prompts in the introduction to the tasks. Whereas we found no differences in learning outcome or extraneous cognitive load, students in the enhanced guidance group reported less intrinsic motivation, and logfiles revealed a lower programming performance. In study 2, we implemented enhanced guidance in the form of adaptive just-in-time explanations for error streaks. Enhanced guidance led to a lower extraneous cognitive load, and this way increased learning outcome.ImplicationsThe type and timing of instructional guidance for students in computer science matters. More guidance is not better in each case. Instructional guidance should be tailored to students’ needs. During online learning, it is essential to provide instructional guidance to support learning. However, guidance can be given in different forms and quantities. Thus, one important challenge is to provide the right amount and type of instructional guidance. The aim of the study is to investigate types of guidance which are effective for students with heterogenous programming knowledge and skills solving programming tasks in a remote laboratory. We carried out two studies with a single factor pre-post-design with guidance (basic/enhanced) as a between-subjects factor. In study 1, we implemented enhanced guidance in the form of prompts in the introduction to the tasks. Whereas we found no differences in learning outcome or extraneous cognitive load, students in the enhanced guidance group reported less intrinsic motivation, and logfiles revealed a lower programming performance. In study 2, we implemented enhanced guidance in the form of adaptive just-in-time explanations for error streaks. Enhanced guidance led to a lower extraneous cognitive load, and this way increased learning outcome. The type and timing of instructional guidance for students in computer science matters. More guidance is not better in each case. Instructional guidance should be tailored to students' needs. Background and Context: During online learning, it is essential to provide instructional guidance to support learning. However, guidance can be given in different forms and quantities. Thus, one important challenge is to provide the right amount and type of instructional guidance. Objective: The aim of the study is to investigate types of guidance which are effective for students with heterogenous programming knowledge and skills solving programming tasks in a remote laboratory. Method: We carried out two studies with a single factor pre-post-design with guidance (basic/enhanced) as a between-subjects factor. Findings: In study 1, we implemented enhanced guidance in the form of prompts in the introduction to the tasks. Whereas we found no differences in learning outcome or extraneous cognitive load, students in the enhanced guidance group reported less intrinsic motivation, and logfiles revealed a lower programming performance. In study 2, we implemented enhanced guidance in the form of adaptive just-in-time explanations for error streaks. Enhanced guidance led to a lower extraneous cognitive load, and this way increased learning outcome. Implications: The type and timing of instructional guidance for students in computer science matters. More guidance is not better in each case. Instructional guidance should be tailored to students' needs. |
Audience | Higher Education Postsecondary Education |
Author | Hawlitschek, Anja Dietrich, André Zug, Sebastian |
Author_xml | – sequence: 1 givenname: Anja surname: Hawlitschek fullname: Hawlitschek, Anja email: Anja.Hawlitschek@ovgu.de organization: Otto-von-Guericke Universität Magdeburg – sequence: 2 givenname: André surname: Dietrich fullname: Dietrich, André organization: Technische Universität Bergakademie Freiberg – sequence: 3 givenname: Sebastian surname: Zug fullname: Zug, Sebastian organization: Technische Universität Bergakademie Freiberg |
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SubjectTerms | Between-subjects design Cognitive Ability Cognitive load Cognitive Processes Computer science Computer Science Education Design factors Distance Education Distance learning Educational objectives Educational Technology Electronic Learning Foreign Countries Guidance Instructional Effectiveness online learning Outcomes of Education Programming remote laboratory Simulated Environment Student Motivation Students Teaching Methods Undergraduate Students |
Title | Effects of different types of guidance on students' motivation and learning in a remote laboratory in computer science |
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