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    Applying multimodal learning analytics to examine the immediate and delayed effects of instructor scaffoldings on small groups’ collaborative programming

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    ; Heidelberg Vol. 9, Iss. 1,  (Dec 2022).     DOI:10.1186/s40594-022-00361-z
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    References (99)

    • 1.
      Stahl, G. (2009). Studying virtual math teams . New York: Springer. Available at http://GerryStahl.net/vmt/book .
    • 2.

      The effect of determining pair programming groups according to various individual difference variables on group compatibility, flow, and coding performance

      O Demir; SS Seferoglu. Journal of Educational Computing Research Vol. 59, Iss. 1, (2020): 41-70.
    • 3.

      The effects of three instructor participatory roles on a small group’s collaborative concept mapping

      Ouyang, Fan; Xu, Weiqi.  Journal of Educational Computing Research Vol. 60, Iss. 4,  (Jul 2022): 930-959.
    • 4.

      Creativity in engineering mathematical models through programming

      Kynigos, Chronis; Diamantidis, Dimitris.  ZDM-MATHEMATICS EDUCATION Vol. 54, Iss. 1,  (Apr 2022).
    • 5.

      Collaborative versus individual problem solving in computational thinking through programming: A meta‐analysis

      X Y Lai; G K W Wong. British Journal of Educational Technology Vol. 53, Iss. 1, (2022): 150-170.
    • 6.

      Influence of scaffolding on information literacy and argumentation skills in virtual field trips and problem-based learning for scientific problem solving

      Kim, N J. International Journal of Science and Mathematics Education Vol. 20, Iss. 2, (2022): 215-236.
    • 7.

      An exploratory study on fade-in versus fade-out scaffolding for novice programmers in online collaborative programming settings

      Zheng, L; Zhen, Y; Niu, J; Zhong, L. Journal of Computing in Higher Education Vol. 34, Iss. 2, (2022): 489-516.
    • 8.

      Examining the effects of three group‐level metacognitive scaffoldings on in‐service teachers' knowledge building

      F Ouyang; S Chen; Y Yang; Y Chen. Journal of Educational Computing Research Vol. 60, Iss. 2, (2022): 352-379.
    • 9.

      Evaluating the impact of the curriculum structure on group metacognition during collaborative problem‐solving using educational robotics

      C Socratous; A Ioannou. TechTrends Vol. 66, Iss. 5, (2022): 771-783.
    • 10.

      Combining sociocultural discourse analysis and multimodal analysis to explore teachers' and pupils' meaning making

      Twiner, A; Littleton, K; Whitelock, D; Coffin, C.  LEARNING CULTURE AND SOCIAL INTERACTION Vol. 30,  (Sep 2021).
    • 11.

      Scaffolding the development of creativity from the students' perspective

      Maksic, Slavica; Josic, Smiljana. THINKING SKILLS AND CREATIVITY; ELSEVIER SCI LTD Vol. 41, (Sep 2021).
    • 12.

      Scaffolding problem solving with learners’ own self explanations of subgoals

      Margulieux, Lauren E; Catrambone, Richard.  Journal of Computing in Higher Education; Dordrecht Vol. 33, Iss. 2,  (Aug 2021): 499-523.
    • 13.

      Improving programming skills through an innovative collaborative programming model: A case study

      L Zheng: Data-driven design for computer-supported collaborative learning, 75-85. 2021.
    • 14.

      Structured or unstructured educational robotics curriculum? A study of debugging in block-based programming

      Socratous, C; Ioannou, A. Educational Technology Research and Development Vol. 69, (2021): 3081-3100.
    • 15.

      International handbook of computer-supported collaborative learning

      Cress, U; Rose, C; Wise, A; Oshima, J: Springer, 2021.
    • 16.

      Keep me in the loop: Real-time feedback with multimodal data

      D Di Mitri; J Schneider; H Drachsler. International Journal of Artificial Intelligence in Education(2021).
    • 17.

      Exploring the effect of three scaffoldings on the collaborative problem-solving processes in China’s higher education

      Ouyang Fan; Chen, Zixuan; Cheng Mengting; Tang Zifan; Chien-Yuan, Su.  International Journal of Educational Technology in Higher Education; Heidelberg Vol. 18, Iss. 1,  (Dec 2021).
    • 18.

      Comparing learners' knowledge, behaviors, and attitudes between two instructional modes of computer programming in secondary education

      Sun, Dan; Ouyang, Fan; Li, Yan; Zhu, Caifeng. International journal of STEM education Vol. 8, Iss. 1, (2021): 54.
    • 19.

      The influence of SRA programming on algorithmic thinking and self‐efficacy using Lego robotics in two types of instruction

      Fanchamps, N. L. J. A; Slangen, L; Hennissen, P; Specht, M. International Journal of Technology and Design Education Vol. 31, Iss. 2, (2021): 203-222.
    • 20.

      Collaboration analytics—current state and potential futures

      B Schneider; N Dowell; K Thompson. Journal of Learning Analytics Vol. 8, Iss. 1, (2021): 1-12.