Programing language typically involves new vocabulary (keywords), punctuation (symbols), and grammatical structures (syntax) that people need to understand in order to communicate with computer. In other words, programming language is like a second language. Just as knowledge of the vocabulary, grammar, and punctuation do not make someone fluent in a spoken language, being a successful programmer requires more than just rote-knowledge. Current introductory programming courses often struggle to provide enough problem solving because so much time is spent on learning the rote elements of the language. By applying the well-developed cognitive frameworks used in second language acquisition (SLA), a Blended Learning (aBLe) course can be developed that will accommodate a variety of learning needs and abilities, while potentially increasing student engagement in online components, reducing the intimidation and anxiety associated with learning programming languages, and providing better preparation for face-to-face classes. SLA-aBLe will emphasize the problem solving needed in other general education courses instead of just keywords, syntax, and symbols. It will encourage the development of problem solving skills needed to persist in their higher education.
This paper describes a design and implementation of a SLA-aBLe project in 2015, which was funded by NSF Research Initiation Grant in Engineering Education (RIGEE) program. This study will test the hypothesis that the use of cognitive frameworks in second language acquisition for the development of a blended learning of programming languages can improve engagement and the learning experience of engineering students. Using this approach will place greater emphasis on problem solving techniques that can be utilized in all courses. The online module consists of a series of short videos (10-20 minutes), online quizzes with tiered questions, and topic specified discussion board led by student researchers. The lab practice time is used to augment the online content through collaborative learning such as think, pair, and share. SLA-aBLe study is emphasized through strategies in five stages defined in SLA theory such as more self-testing tiered questions and visual-aided explanation in the screencasts, more online programming writing assessment, more collaboration, and ‘speak aloud’ in the lab. Student’s demographic data, course-related behaviors such as usage of the instructional videos and discussion board, student performance such as quizzes, and exams, attitude toward the class will be compared across students in the SLA-aBLe, and control groups to determine if student performance, behavior and attitudes vary across classrooms employing different teaching strategies.
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