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This paper presents a systematic literature review of professional development programs in Computational Thinking. Computational thinking (CT) has emerged as an essential set of skills that everyone should develop to participate in a global society. However, there were no pre-service or in-service teacher programs to integrate CT into the K-12 classrooms until very recently. Thus, it is important to identify how educators and researchers address the challenges to prepare the next generation of students and what gaps persist in the current literature. We review existing work in this field from two perspectives: First, we analyze the learning outcomes, assessment methods, pedagogical approaches, and pedagogical tools used in the Professional Development programs in CT. Second, we examine how these programs assess the teachers’ knowledge and skills as outcomes. We used the technological pedagogical and content knowledge (TPACK) framework to characterize existing literature and identify possible gaps in the preparation of pre-service and in-service teachers in CT. Our results suggest that: (1) existing evidence is limited to developed countries; (2) many studies are only focusing on teachers understanding the concepts but do not explore how the participants evaluate or create learning activities; (3) no studies look into classroom observations as part of the program, which limits our understanding to how these programs work; and (4) most programs use block-based programming languages as the tool to develop student computational thinking. While block-based programming languages are used for introductory training programs, students are often expected to transfer their learning to more professional programming languages.
This paper presents a systematic literature review of professional development programs in Computational Thinking. Computational thinking (CT) has emerged as an essential set of skills that everyone should develop to participate in a global society. However, there were no pre-service or in-service teacher programs to integrate CT into the K-12 classrooms until very recently. Thus, it is important to identify how educators and researchers address the challenges to prepare the next generation of students and what gaps persist in the current literature. We review existing work in this field from two perspectives: First, we analyze the learning outcomes, assessment methods, pedagogical approaches, and pedagogical tools used in the Professional Development programs in CT. Second, we examine how these programs assess the teachers’ knowledge and skills as outcomes. We used the technological pedagogical and content knowledge (TPACK) framework to characterize existing literature and identify possible gaps in the preparation of pre-service and in-service teachers in CT. Our results suggest that: (1) existing evidence is limited to developed countries; (2) many studies are only focusing on teachers understanding the concepts but do not explore how the participants evaluate or create learning activities; (3) no studies look into classroom observations as part of the program, which limits our understanding to how these programs work; and (4) most programs use block-based programming languages as the tool to develop student computational thinking. While block-based programming languages are used for introductory training programs, students are often expected to transfer their learning to more professional programming languages.
In the Czech Republic, a new concept that proposes an Informatics curriculum for primary schools was prepared to meet the new requirements of the field. For the implementation to be smooth, a two-year transition period was planned from 2021 to 2023. Training seminars were the main tool to help teachers develop missing subject knowledge and didactic skills. After the first year of the transition period, the question was whether the seminars met the needs of teachers. Therefore, the main objective of the investigation was to collect feedback from them (N = 142) in five regions (of 14), consider changes within the first year (from autumn 2021 to autumn 2022), and propose recommendations for the rest of the period (by autumn 2023). The ex post facto method was used. Data were collected by questionnaires in five areas: (1) preference for an original or new concept for a curriculum, (2) and subject knowledge and didactic skills of teachers, (3) school equipment; (4) learning materials and teaching methods used, and (5) experience in online learning and teaching. The results show that in autumn 2022, the support for the new concept increased and the school equipment improved; however, subject knowledge and didactic skills were the weak points. Individualization through the tailoring of the seminars to the needs of teachers represents an efficient way to train them according to their level of knowledge, their preferred form of learning, and the learning content.
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