Digital smart board is one of interactive technology tools which has been used widely in schools to facilitate teaching and learning. Empirical evidence shows that digital smart board allows students to construct their knowledge while mastering more advanced thinking skills. Thus integration of digital smart board facilitates active learning, which is fundamental to mastery of skills. Active learning using smart board program is a program which integrates smart board in Data Handling so that primary school students can learn Data Handling concept actively and meaningfully. Therefore, this study was conducted to identify the effectiveness of active learning using smart board program to enhance primary school students’ learning. Five experts in teaching Mathematics Education and thirty year five students were involved in this study. The students were selected based on purposive sampling. This study used both quantitative and qualitative research approach. A set of interview protocol and a set of questionnaire were used during the data collection phase. Findings from the questionnaire were analysed based on descriptive and inferential statistics by using Winsteps Version 3.72.3. In addition, thematic analysis was used to analyse the qualitative data. Findings from the study indicate that active learning using smart board program has the attributes which can effectively enhance primary school students’ learning. It is hoped that the results from this study can contribute towards development of active learning strategies, methods or activities using smart board in order to enhance primary students’ learning in school.

Data Handling at primary school involves gathering and recording information and then presenting it in a way that is meaningful to others. It is a fundamental part of student's mathematical understanding. Initial concepts of Data Handling need to be exposed to students in the early years as these skills will be used and built upon throughout their education. Due to its importance, Data Handling is included in the curriculum at primary level in Malaysia. However results of international assessments which focused on the use of higher order thinking skills showed that Malaysian students performed poorly in Data Handling. Therefore, this study was conducted to identify students’ learning difficulties in Data Handling at each level of higher order thinking skills (HOTS) namely applying, analysing, evaluating and creating. In addition, this study also investigated the use of smart board in overcoming HOTS learning difficulties in Data Handling. Numerous teachers recommend the use of smart board at primary schools since students have the opportunity to explore and learn novel concepts using the technology. Subsequently, it helps to generate dynamic learning experiences and student in school become more motivated about learning when the smart board is used during their lessons. Four experienced year five mathematics teachers and thirty year five students from a primary school were involved in the study. The students and teachers were selected based on purposive sampling. An interview protocol and rubric for cognitive domain in HOTS were used during the data collection phase. In addition, semi-structured interview sessions with the teachers and students as well as document analysis of the students’ mathematics exercise sheets in Data Handling were carried out by the researcher to investigate the students’ learning difficulties at each level of HOTS in Data Handling. It is hoped that the results from this study can contribute towards development of strategies, methods or programs using smart board to enhance HOTS in Data Handling among primary school students in Malaysia.

No abstract

Data Handling is an important topic in the Mathematics Primary Curriculum as it brings the real world of seeing data to students. However, the assessments of PISA and TIMSS indicated that the level of Malaysian students' performance and Higher Order Thinking Skills (HOTS) in Data Handling is declining. Thus, this study was designed to develop active learning instructions using smart board (ALuSB programme) and to evaluate its effectiveness in enhancing HOTS among Malaysian students in Data Handling. The study was carried out in two stages; the design and development of ALuSB programme stage based on ADDIE model and the evaluation stage to see the enhancement of HOTS in Data Handling. The research design adopted for this study was a pre-test post-test quasi-experimental design using non-equivalent control group. Quantitative and qualitative data were collected for analyses. The quantitative data was analysed using One-way ANOVA to evaluate the mean differences between the treatment groups whereas a post hoc test was further used to determine precisely which mean differences were significant and visa-versa among all the three groups. Additionally, the qualitative data was analysed using thematic analysis. The findings in this study indicated that ALuSB programme has the potential to improve students' performance and HOTS in Data Handling. Students also demonstrated increase in their ability to carry out a procedure, differentiate and organise data, make judgments and create a table or graph, making the ALuSB programme suitable to be applied in schools as it can effectively help students to enhance their HOTS.

Several studies on metacognition have sought to solve mathematical problems. However, in Malaysia, there has yet to be a study investigating the metacognitive behaviour of students in solving mathematical problems of Form Three Assessment (Pentaksiran Tingkatan Tiga -PT3). This study was conducted to identify the metacognitive behaviour of students while solving mathematical problems in PT3 and examine differences in metacognitive behaviour among successful students (SS), partially successful students (PSS), and unsuccessful students (USS). A total of six (6) Form Three students in a school in Johor Bahru participated in this study. The research instrument used was the actual set of 2014's PT3 questions. Data were analysed using the Thinking Aloud method with reference to Foong's Taxonomy (1993), and it was supported by analysis of the students' written work. Results showed seven types of metacognitive behaviour exhibited by the students, depending on the types of questions given. The analysis also found that each category of students showed different types of metacognitive behaviour while solving their PT3 mathematical problems. The SS group could control their metacognitive behaviour in mathematical problem-solving more regularly and frequently, the PSS students behaved moderately, while the USS group demonstrated limited metacognitive behaviour. As the results indicated differences in metacognitive behaviour among students of different performance levels, teachers should help students with weakness in solving mathematical problems implement metacognitive behaviour to strengthen their mathematical proficiency.