A Framework and an Instructional Design Model for the Development of Students\u27 Computational and Algorithmic Thinking

The authors herein, describe their efforts towards designing technology-enhanced instruction for teaching Computational and Algorithmic Thinking. This study examined students’ development of Computational and Algorithmic Thinking, by utilizing the framework of Technological Pedagogical Content Knowledge and the instructional design model of Technology Mapping. Different technological tools were used for both groups of participants; the experimental and the control group. In particular, the experimental group used educational robotics and the control group used a 3D interactive programming environment. Both groups were 8th graders coming from different secondary education schools in Cyprus. A pre-post test research design was adopted in each classroom intervention. To check whether the interventions facilitated students’ development and understanding of Computational and Algorithmic Thinking concepts and competencies, an analysis of covariance (ANCOVA) was then conducted. According to the results, the framework of Technological Pedagogical Content Knowledge and the approach of Technology Mapping, which guided the design of the instructional intervention were effective in terms of fostering students’ development and understanding of Computational and Algorithmic Thinking competencies and concepts, respectively

Computational Thinking Integration into Middle Grades Science Classrooms: Strategies for Meeting the Challenges

This paper reports findings from the efforts of a university-based research team as they worked with middle school educators within formal school structures to infuse computer science principles and computational thinking practices. Despite the need to integrate these skills within regular classroom practices to allow all students the opportunity to learn these essential 21st Century skills, prior practice has been to offer these learning experiences outside of mainstream curricula where only a subset of students have access. We have sought to leverage elements of the research-practice partnership framework to achieve our project objectives of integrating computer science and computational thinking within middle science classrooms. Utilizing a qualitative approach to inquiry, we present narratives from three case schools, report on themes across work sites, and share recommendations to guide other practitioners and researchers who are looking to engage in technology-related initiatives to impact the lives of middle grades students

The Effect of Group Interactions and Group Structure on Achievement in Elementary School Robotics Classrooms

Jung and Won\u27s (2018) review of elementary school ER found a lack of understanding of instructional practices for ER with young children. Other researchers have called for further studies into what effective classroom orchestration and interaction look like within ER classrooms (Ioannou & Makridou, 2018; Xia & Zhong, 2019). This study was conducted to understand the effect of group interactions and group structure in terms of gender on achievement in elementary school robotics classes. Knowing the effect that interactions have on students\u27 achievement can help inform instructional practices and pedagogies in educational robotics activities (Kucuk & Sisman, 2017). The study was conducted at a primary school in Nonthaburi, Thailand. The participants included 103 second-grade students (44 male, 59 female). A mixed methods embedded research design was used as a framework to make observations of interactions, conduct a robotics assessment, and analyze the data from the assessment. Cooperative learning (CL), which is the use of instructional small groups to maximize learning (Johnson et al., 1999) was used as a lens for observing student interactions. Group processing, positive interdependence, and promotive interactions are some of the primary elements of CL and used as classifications of student interactions in the robotics classrooms and during the assessment. The robotics assessment consisted of multiple challenges where students were given a score in their skills of generalization, algorithmic thinking, and their Level of Achievement (LoA). The LoA was the sum of all the challenges completed. The mean scores of the students’ assessment results were analyzed using separate one-way ANOVAs to explore the effect of group structure and interaction types on achievement. It was found that the types of interactions in a group can have an effect on achievement depending on the types of robotics challenges. It was also found that gender did not have an effect on the student\u27s LoA during their robotics assessment, but it did have an effect on the types of interactions seen among students. It is recommended that for simpler robotics challenges that utilize basic generalization skills, instructors should try to facilitate promotive interactions within the classroom groups. For more advanced robotics challenges that utilize algorithmic thinking skills, instructors should try to facilitate group processing within their classroom groups

A Literature Review for the Implementation of Computational Thinking for Ontario K-12 Classrooms

The importance of the problem-solving skills involved in computational thinking has gained significant traction since its introduction. As Ontario seeks to implement coding into the school curriculum, an analysis of previous implementation of computational thinking could provide a framework for which to formulate new curriculum in the province. A literature review was completed to investigate the following three questions: (1) How has computational thinking been implemented into education in a K-12 environment? (2) What barriers will affect the implementation of computational thinking in a K-12 environment? (3) What grade levels are appropriate for implementing the varying competencies of computational thinking? This literature review sheds light on the need for teacher support, the political implications involved in introducing new curriculum, and where computational thinking best fits into current K-12 curriculum

The Need to Integrate Computer Science

This school improvement plan outlines a detailed three-year strategy designed to integrate computer science into the K-5 curriculum. Emphasizing a comprehensive approach, the action plan employs a multi-tiered strategy combining a standalone curriculum with embedded activities. Drawing insights from successful educational practices and leveraging resources, the plan strategically aligns the curriculum with CSTA standards while fostering hands-on learning experiences at various grade levels. The timeline features foundational teacher training, curriculum integration, community engagement events, and consistent assessment processes. The plan aims to create an environment where both students and educators actively participate in the dynamic landscape of computer science education. By using a phased approach, this blueprint offers a comprehensive understanding of computer science concepts, equipping students for success in a technology-driven world. The plan acknowledges the importance of monitoring potential barriers and challenges to ensure effectiveness in the integration process

Investigating an Instructional Model for Integrated STEM in Teacher Education

Active learning experiences that incorporate technology, design, and making combine to form an important and necessary pedagogical approach that supports the 21st century skills of collaboration, communication, creativity, digital literacies, and computational thinking as a problem-solving framework. Active learning experiences in teacher preparation serve as a model for future educators to follow, while building the educators\u27 efficacy to conduct future implementations with their own students. In this study, a multidisciplinary Pop-Up Makerspaces activity was conducted as an active hands-on approach to interdisciplinary STEM education. The intersectionality of English language arts with integrated STEM through design and making included: (a) enriching language and integrated STEM literacy, (b) scaffolding and supporting pre- and inservice educators through well-designed active learning as these opportunities help to develop self-efficacy, and (c) exploring new models and frameworks for transdisciplinarity

Learning to Code: Effects of Programming Modality in a Game-based Learning Environment

As new introductory block-based coding applications for young students to learn basic computer science concepts, such as, loops and conditionals, continue to increase in popularity, it is necessary to consider the best method of teaching students these skills. Many of these products continue to exhibit programmatic misconceptions of these concepts and many students struggle with how to apply what they learn to a text-based format due to the difficulties with learning the syntactic structure not present in block-based programming languages. If the goal of teaching young students how to program is meant to develop a set of skills they may apply when learning more complex programming languages, then discerning how they are introduced to those practices is imperative. However, few studies have examined how the specific modality in which students are taught to program effects how they learn and what skills they develop. More specifically, research has yet to effectively investigate modality in the context of an educational coding game where the modality feature is controlled, and content is consistent throughout game-play. This is mainly due to the lack of available games with this feature designed into the application. This dissertation explores whether programming modality effects how well students can learn and transfer computer science concepts and practices from an educational programming game. I proposed that by being guided from a blocks-based to text-based programming language would instill a deeper understanding of basic computer science concepts and would support learning and improve transfer and performance on new challenging tasks. Two experimental studies facilitated game-play sessions on the developed application for this project. The first study was a 2x2 between subjects design comparing educational module (game versus basic) and programming modality (guided versus free choice). The findings from Study 1 informed the final version design for the module used in the second study where only the game module was used in order to focus the comparison between programming modality. Findings showed that students who coded using the game module performed better on a learning test. Study 2 results showed that students who are transitioned from blocks-based to text-based programming language learn basic computer science concepts with greater success than those with the free choice modality. A comparative study was conducted using quantitative data from learning measures and qualitative video data from the interviews during the challenge task of the second study. This study examined how students at the extreme levels of performance utilized the toggle switch feature during game-play and how the absence of the feature impacted how they completed the challenge task. This analysis showed two different methods of toggle switch usage being implemented by a high and low performing student. The high performing student utilized the resources more often during the challenge tasks in lieu of leveraging the toggle switch and were still able to submit high level code. Results suggest that a free choice student who uses the feature as a tool to check their prewritten code rather than a as short cut for piecing code together as blocks and submitting the text upon the final attempt. This practice leads to a shallower understanding of the basic concepts and make it extremely difficult to expand and apply that knowledge to a more difficult task. This dissertation includes five chapters: an introduction and theoretical framework, a game design framework and implementation description, two experimental investigations, and a quantitative and qualitative comparative analysis. Chapter one provides the conceptual and theoretical framework for the two experimental investigations. Chapter two describes the theory and design structure for the game developed for this dissertation work. Chapter three and four will discuss the effects of programming modality on learning outcomes. Specifically, chapter 3 focuses on implications of programming modality when determining how to implement changes for the design of the game for Study 2. Chapter five discusses a comparative analysis that investigated differing work flow patterns within the free choice condition between high and low performing students. Results from these three chapters illustrate the importance of examining this component of the computer science education process in supplemental games for middle and high school students. Additionally, this work contributes in furthering the investigation of these educational games and discusses implications for design of similar applications