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AMOEBA: Designing for collaboration in computer science classrooms through live learning analytics

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Abstract

AMOEBA is a unique tool to support teachers’ orchestration of collaboration among novice programmers in a non-traditional programming environment. The AMOEBA tool was designed and utilized to facilitate collaboration in a classroom setting in real time among novice middle school and high school programmers utilizing the IPRO programming environment. AMOEBA’s key affordance is supporting teachers’ pairing decisions with real time analyses of students’ programming progressions. Teachers can track which students are working in similar ways; this is supported by real-time graphical log analyses of student activities within the programming environment. Pairing students with support from AMOEBA led to improvements in students’ program complexity and depth. Analyses of the data suggest that the data mining techniques utilized in and the metrics provided by AMOEBA can support instructors in orchestrating cooperation. The primary contributions of this paper are a set of design principles around and a working tool for fostering collaboration in computer science classes.

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Notes

  1. Within the literature of pair programming understanding, competence, aptitude, and skill are frequently used near synonymously. Here the term “skill” will be used for this amalgam and the term “proficiency” will be used for a superset of skill and contextual comprehension.

  2. IPRO is available free of charge on the iTunes store.

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Acknowledgments

Thanks to the Complex Play Lab for helping refine this work. This work was supported by National Science Foundation Grant No. 1331655. The opinions expressed in this paper are those of the authors and do not necessarily represent those of the NSF.

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Authors and Affiliations

  1. Department of Curriculum and Instruction, University of Wisconsin–Madison, 225 N. Mills Street, Madison, WI, 53706-1795, USA

    Matthew Berland

  2. Department of Interdisciplinary Learning & Teaching, University of Texas at San Antonio, San Antonio, TX, USA

    Don Davis

  3. Department of Education, University of Vermont, Burlington, VT, USA

    Carmen Petrick Smith

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Correspondence to Matthew Berland.

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Berland, M., Davis, D. & Smith, C.P. AMOEBA: Designing for collaboration in computer science classrooms through live learning analytics. Intern. J. Comput.-Support. Collab. Learn 10, 425–447 (2015). https://doi.org/10.1007/s11412-015-9217-z

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