Scratchthai+ : a precision education-based learning support framework for computational thinking development | |
| Author | Kantinee Katchapakirin |
| Call Number | AIT Diss no.CS-22-02 |
| Subject(s) | Artificial intelligence--Educational applications Artificial intelligence--Study and teaching Computer science--Study and teaching Scratch (Computer program language) |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science |
| Publisher | Asian Institute of Technology |
| Abstract | Computational Thinking (CT) is officially introduced into the National Curriculum worldwide. Scratch, a block-based visual programming language, is widely adopted in primary-level schools. However, traditional learning support systems lack important capabilities to support CT teaching and learning in a regular classroom. Recent CT development through programming in formal education has presented three important challenges: P1: Mixed-ability students in the same class, P2: a high student-teacher ratio, and P3: a learning-hour limitation. To effectively address the challenges, this research proposes ScratchThAI+ framework to enhance CT teaching and learning through Scratch programming. The framework provides a kid-friendly chatbot and precision education features (i.e., assessment, treatment, and prevention) to the Scratch website. The chatbot assists diverse students in learning and practicing online coding anywhere, anytime. The assessment analyzes students’ learning activities and products throughout their practice. CT competency and difficulties are recognized for both individuals and the class as a whole. The treatment and prevention feature then initially intervene by suggesting extra exercises and learning materials, to fill the gaps. The framework provides a dashboard to visualize students’ learning progress and learning performance. This enables teachers to identify at-risk students earlier and manage appropriate interventions within the constraints of limited school hours. The research is organized into three phases with three objectives: (1) understanding traditional classroom practices and challenges in CT development and assessment, (2) designing and developing a teaching and learning support framework for precision CT education, and (3) developing a precision education-based assessment by adopting evidence-based approaches. The first phase explores Thai school challenges, importance, and strategies using case studies and a survey. The case studies reveal teachers’ opinions on challenges and strategies. The survey determines the top five challenges. Then, we address the three challenges (P1-P3). The second phase designs and develops ScratchThAI, a conversation-based learning support framework, which adopts relevant educational approaches and relevant technology-enhanced learning (TELs) in its design and architecture to address the challenges. ScratchThAI is adopted as part of Grade 5’s computing science course in a Thai primary school. The results reveal that it can alleviate the challenges with the following supports: achieving better learning performance, enhancing teaching, and learning activities, promoting student engagement and motivation and positive teachers’ and students’ satisfaction. The third phase designs PLUS assessment model which adopts an evidence-based approach into its design and integrates with ScratchThAI, called ScratchThAI+. ScratchThAI+ collects evidence throughout students’ practice (i.e., evidence of the learning process and final products in problem-solving phase and programming phase) and analyzes it against a predefined rule-based system. This enables the provision of accurate and timely assessment information, which is hard to achieve in traditional classroom practices. We investigate ScratchThAI+ effectiveness in an online workshop context and compare its assessment results with traditional automatic assessment. The acquired results present more accurate grading, precise identified mastery and difficulty, earlier identify at-risk students, and provide better understanding of students’ learning. Thus, ScratchThAI+ contributes as a possible and practical solution to CT development and CT education improvement under the aforementioned challenges and also illustrates benefit of adopting precision education in practice. |
| Year | 2022 |
| Type | Dissertation |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Computer Science (CS) |
| Chairperson(s) | Chutiporn Anutariya |
| Examination Committee(s) | Dailey, Matthew N.;Chaklam Silpasuwanchai;Thepchai Supnithi |
| Scholarship Donor(s) | Royal Thai Government;AIT Fellowship |
| Degree | Thesis (Ph.D.) - Asian Institute of Technology, 2022 |