Scratchxchange : a platform for personalized, adaptive, shareable and composable scratch learning | |
| Author | Rungtiwa Fordsungnoen |
| Call Number | AIT Thesis no.CS-22-01 |
| Subject(s) | Scratch (Computer program language)--Study and teaching Individualized instruction--Data processing |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science |
| Publisher | Asian Institute of Technology |
| Abstract | In addition to logical reasoning, computer programming is seen as a crucial talent for the development of problem-solving abilities. A number of basic programming environments have been developed to assist newbies in avoiding typical programming errors such as gram mar and logic. Most of these breakthrough environments use block-based programming languages rather than inputting instructions for example, Scratch which the instructive and entertaining activities offered and a free and open-source programming language. However, computer programming is a difficult course to teach and learn. the learning process differs for different learners, depending on their personality, cognitive abilities, and past learning experiences. To support student’s differences, an personalized and adaptive mechanism are need to gen erate individual suggestions. In this thesis, students were assigned practice exercises and suggesting related learning resources based on the characteristics and performance. More over, the learner profiles, shareable and composable scratch learning resources and learning path were modeled from comparing various metadata standard models to support above mechanism. For recommendation, Rules-Based Personalization were used for mapping the student personal profile and learning object. The evaluation of this thesis are divided into two parts: student experiment and teacher feedback from interview. The purposes experiment are measuring the 1) Educational met rics or Knowledge assessment which comparing average performance improvement between two groups; 2) User-centric by filling USE questionnaire (satisfaction) and 3) calculating the accuracy of suggestions of ScractchXChange by using teacher’s opinion. As a result, ScractchXChange can recommend learning resources that meet with student need as stu dents satisfied with the system as well as all students have gain score. In addition, the average accuracy suggestions Personalization Module from teachers is in good level accuracy. |
| Year | 2022 |
| Type | Thesis |
| 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; |
| Scholarship Donor(s) | Royal Thai Government,; |
| Degree | Thesis (M. Sc.) - Asian Institute of Technology, 2022 |