Predicting Students' Attitudes Toward Collaboration: Evidence From Structural Equation Model Trees and Forests

Abstract

Numerous studies have shed some light on the importance of associated factors of collaborative attitudes. However, most previous studies aimed to explore the influence of these factors in isolation. With the strategy of data-driven decision making, the current study applied two data mining methods to elucidate the most significant factors of students' attitudes toward collaboration and group students to draw a concise model, which is beneficial for educators to focus on key factors and make effective interventions at a lower cost. Structural equation model trees (SEM trees) and structural equation model forests (SEM forests) were applied to the Program for International Student Assessment 2015 dataset (a total of 9,769 15-year-old students from China). By establishing the most important predictors and the splitting rules, these methods constructed multigroup common factor models of collaborative attitudes. The SEM trees showed that home educational resources (split by “above-average or not”), home possessions (split by “disadvantaged or not”), mother's education (split by “below high school or not”), and gender (split by “male or female”) were the most important predictors among the demographic variables, drawing a 5-group model. Among all the predictors, achievement motivation (split by “above-average or not”) and sense of belonging at school (split by “above-average or not” and “disadvantaged or not”) were the most important, drawing a 6-group model. The SEM forest findings proved the relative importance of these variables. This paper discusses various interpretations of these results and their implications for educators to formulate corresponding interventions. Methodologically, this research provides a data mining approach to discover important information from large-scale educational data, which might be a complementary approach to enhance data-driven decision making in education.

A Crowd–AI Collaborative Approach to Address Demographic Bias for Student Performance Prediction in Online Education

“…In particular, X D i for i ∈ {1, 2, ..., I} represents the demographic attribute category of the i th student, where X D i ∈ {D 1 , D 2 , ..., D M }. Demographic data are widely used in student performance prediction (Kuzilek, Hlosta, and Zdrahal 2017;Adnan et al 2021;Waheed et al 2020;Fancsali et al 2018) due to its criticality in predicting each student's performance accurately (Li et al 2021;Sabnis, Yu, and Kizilcec 2022), though the use of such data is often debated (Baker and Hawn 2022). Moreover, the demographic bias often stems from the lack of data and difference in behavior of underrepresented groups instead of the demographic information itself (Baker and Hawn 2022), as explained in the Introduction section.…”

A Socioculturally Microgenetic Scrutiny on the Mediational Role of Teacher/Peer Scaffolding via Dialogic Collaboration in EFL Speaking Development

“…Many studies have addressed different scaffolding features of the collaboration with different characteristics. Anton and Di Camilla (1999), Budiartha andVanessa (2021), Di Camilla &Anton (1997), Lantolf and Aljaafreh (1995), Li, Zhang, Li, Huang and Shao (2021), Pata, Sarapuu, and Lehtinen (2005), Razaghi, Bagheri, andYamini (2019), Saetra (2021), and Yelland and Masters (2005), among many others, have studied the mediating nature of collaborative dialogue in fulfilling different kinds of tasks. For instance, Anton and Di Camilla (1999) examined the use of L1 as a powerful tool of semiotic mediation in providing scaffolded help in the collaborative activities.…”

Developing of Collaboration Skill in Media Using Closing Statement of Dahlan Iskan Notes on Covid-19

“…The demands of the times required everyone to improve the skills of collaborating with others. Some studies suggest that collaboration improves relationships between team members, results in evaluations for partners, and improves performance [8]. Therefore, collaboration activities are not just coming together to solve problems or share information.…”