A Practice for Providing Additional Support in CS1

Abstract

This paper reports on a practice used for providing additional support to beginner programmers. This practice emphasizes low social barriers to learning, differentiated instruction, and revision. Altogether we try to avoid defensiveness or stigmatization among those who face difficulties. Student feedback indicates their acceptance of this approach while teaching assistants report that helping students in need of additional support improve their teaching skills. Further, we have observed indications of improved student performance. We describe the practice and suggest a particular educational constructionism, i.e., how students construct their social identities within a particular school setting, as an explanation for our positive experiences. As a conclusion, we stress the importance of support implemented through differentiated instruction and informed by constructionism as a CS1 research topic.

Introductory programming: a systematic literature review

“…For example, Barker et al [46] found that factors such as peer interaction predicted intention to continue studying computing, and Schoeffel et al [576] found correlations between social motivation and performance. Other researchers such as Haatainen et al [234] considered social barriers such as whether students felt comfortable requesting help. Indeed, many such social integration challenges have been identified in the literature.…”

Types and time of interaction for teaching introductory programming using instruction method of extreme apprenticeship

“…The students were predominantly taught online using online google hangouts, and the activities were coordinated using google classroom and online git version control system. Haatainen et al (2013) have described the implementation of additional support for students finding the CS1 course difficult. In the study, they used self-assessment to identify students needing help.…”

Flipped Learning With Peer Reviews in the Introductory CS Course

“…Consequently, in the very beginning of the studies the amount of support should be at its greatest. For example, in the first computer science courses at university (CS1), the number of dropouts has been successfully decreased with well-designed scaffolds (Haatainen, Lakanen, Isomöttönen, and Lappalainen, 2013). The successful dropout interventions include innovative systems to predict dropout, early intervention and follow-up (Whitehill, Williams, Lopez, Coleman, and Reich, 2015), and beside decreasing the number of dropouts, learning analytics can be utilized to improve the quality of education and to enable students to review and evaluate their own progress (Sclater, Peasgood, and Mullan, 2016).…”