A framework of metacognitive scaffolding in learning through facebook

Abstract

The purpose of this study is to develop a framework of metacognitive scaffolding in learning through Facebook. A quantitative research design of a multiple-case study method was adopted in this research. Initially, a survey was conducted to identify student’s metacognitive abilities. 80 master degree students from the Educational Technology Program were randomly selected to answer the survey. Next, 37 students from the earlier survey were selected as respondents, which further contributed to the development of the framework. These 37 students comprised three cohorts of students from three subsequent semesters. The study identified the dominant mechanism of metacognitive scaffolding prompted by the instructor, along with the dominant types of online interaction triggered by the students in an online discussion. The data was analyzed by using content analysis technique. Besides that, 4 mobile applications or apps were developed by the researcher as the technological tool used in the learning. The mobile apps as well as the learning activities used in the current study follow the project-based learning approach. Data was collected from a General Metacognition Questionnaire (GMQ) survey, observation through Facebook discussions and through a performance test. The results show that the students’ metacognitive abilities in learning are high (µ=3.86). Besides that, this study points out that the instructor often guides the students to focus on their learning process. The findings also demonstrate that students often give opinions rather than giving examples from their existing ideas; they are also unlikely to compare similarities and differentiate facts. Pearson correlation analysis shows a significant correlation between metacognitive scaffolding and students’ types of online interaction with the students’ learning performance. A data mining analysis using a decision tree technique was used to project a predictive model in order to suggest the mechanisms of metacognitive scaffolding appropriate to be used by the instructor; such a technique must be able to contribute to students’ performance in learning. Finally, the proposed framework recommends a series of rules that serves as a shortcut for the instructor to produce meaningful learning among students through metacognitive scaffolding. These rules were derived from data mining, i.e, association rule analysis. These rules also mentioned the types of student online interactions that actually represent their learning process, particularly in terms of their interactivity in Facebook discussions.