Increasing Commuter Students’ Sense of Belonging with Situated Learning in a First-year Computer Programming Course.

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Title: Increasing Commuter Students’ Sense of Belonging with Situated Learning in a First-year Computer Programming Course.
Authors: Liang, Lily R.1 lliang@udc.edu, Kan, Rui2 rui.kang@gcsu.edu
Source: International Journal for the Scholarship of Teaching & Learning. Nov2024, Vol. 18 Issue 2, p1-11. 11p.
Subject Terms: *Computer science students, *Cognitive styles, *Computer programming, *Learning communities, Professional identity
Abstract: This study examines the impact of a situated learning class framework on student learning and sense of belonging in a first-year introductory computer programming course offered at an urban commuter campus. The framework provided students opportunities to engage in hands-on activities embedded in authentic contexts facilitated or led by students from computer science clubs and a service-learning program. Our results suggest that 1) participation in peer interactions within the classroom helped students build learning communities and networks beyond the classroom and strengthened their development of a professional identity; 2) through redesigning curriculum and pedagogy to accommodate students’ needs and learning styles, college and university faculty may cultivate a collaborative culture and a sense of belonging at various levels: classroom, department, and campus. [ABSTRACT FROM AUTHOR]
Copyright of International Journal for the Scholarship of Teaching & Learning is the property of Georgia Southern University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Increasing Commuter Students’ Sense of Belonging with Situated Learning in a First-year Computer Programming Course.
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  Data: <searchLink fieldCode="AR" term="%22Liang%2C+Lily+R%2E%22">Liang, Lily R.</searchLink><relatesTo>1</relatesTo><i> lliang@udc.edu</i><br /><searchLink fieldCode="AR" term="%22Kan%2C+Rui%22">Kan, Rui</searchLink><relatesTo>2</relatesTo><i> rui.kang@gcsu.edu</i>
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  Data: *<searchLink fieldCode="DE" term="%22Computer+science+students%22">Computer science students</searchLink><br />*<searchLink fieldCode="DE" term="%22Cognitive+styles%22">Cognitive styles</searchLink><br />*<searchLink fieldCode="DE" term="%22Computer+programming%22">Computer programming</searchLink><br />*<searchLink fieldCode="DE" term="%22Learning+communities%22">Learning communities</searchLink><br /><searchLink fieldCode="DE" term="%22Professional+identity%22">Professional identity</searchLink>
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  Data: This study examines the impact of a situated learning class framework on student learning and sense of belonging in a first-year introductory computer programming course offered at an urban commuter campus. The framework provided students opportunities to engage in hands-on activities embedded in authentic contexts facilitated or led by students from computer science clubs and a service-learning program. Our results suggest that 1) participation in peer interactions within the classroom helped students build learning communities and networks beyond the classroom and strengthened their development of a professional identity; 2) through redesigning curriculum and pedagogy to accommodate students’ needs and learning styles, college and university faculty may cultivate a collaborative culture and a sense of belonging at various levels: classroom, department, and campus. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal for the Scholarship of Teaching & Learning is the property of Georgia Southern University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.20429/ijsotl.2024.180203
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        Text: English
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        Type: general
      – SubjectFull: Cognitive styles
        Type: general
      – SubjectFull: Computer programming
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      – SubjectFull: Learning communities
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      – SubjectFull: Professional identity
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              Text: Nov2024
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