BLENDED LEARNING ENGAGEMENT IN HIGHER EDUCATION INSTITUTIONS: A DIFFERENTIAL ITEM FUNCTIONING ANALYSIS OF STUDENTS’ BACKGROUNDS

Abstract

Purpose – Digital technology has transformed teaching and learning in such a way that it seems imperative lecturers and institutions need to adapt and adopt a blended learning model of instruction across disciplines. However, there is a scarcity of studies to determine the degree of students’ engagement on blended or online university courses. The purpose of the study is to investigate students’ cognitive engagement, emotional engagement, and behavioural engagement in a blended learning model of instruction as well as specifically assess their engagement based on demographic factors such as age, gender, field of study, ethnicity, and type of institution in leading Malaysian public and private higher education institutions. Methodology – A non-experimental quantitative research design was employed in this study. 462 undergraduate and postgraduate students were sampled using the Blended Learning Readiness Engagement Questionnaire©. Subsequently, WINSTEPS Rasch model measurement software was used to determine the reliability and validity of the research instrument. Descriptive statistics and differential item functioning (DIF) were conducted to assess students’ engagement in a blended learning model of instruction with the latter analysing specifically on student’s demographic factors such as age, gender, field of study, ethnicity, and type of institution. Findings – Findings show high levels of engagement in blended learning activities among students in both public and private higher education institutions based on their cognitive, emotional, and behavioural engagement processes. Findings also indicates differences in students’ engagement based on demographic factors such as age, gender, field of study, ethnicity, and type of institution. Significance –The findings of this study will help lecturers reflect on their own teaching practices in this era of technology advancement where a blended learning model of instruction are given increased prioritisation and proliferation. Implications and recommendations for future research in blended learning practices are presented.

Evaluating item difficulty patterns for assessing student misconceptions in science across physics, chemistry, and biology concepts

“…DIF analysis was performed to assess differences in item function on the basis of gender and grade on all items in test. DIF analysis investigated item responses on the basis of categorical variables for each item on assessing student misconceptions using a test ( Adams et al., 2020 ; Boone et al., 2013 ). Differential item functioning analysis is categorized into three types: moderate to large (| DIF | ≥ 0.64 logits), slight to moderate (| DIF | ≥ 0.43 logits), and negligible ( Zwick et al., 1999 ).…”

Students’ readiness for blended learning in a leading Malaysian private higher education institution

“…However, the readiness of students must be taken into consideration first. We might be heading towards implementation failure without first identifying student readiness, competence and needs (Adams et al, 2018(Adams et al, , 2020Kintu et al, 2017). Lecturers must know how to design courses that promote online learning while maintaining control.…”

“…Educators agree that blended learning promotes continuity in learning which translates into better grades amongst students, and successfully impacts overall gain in skills and knowledge (Adams et al, 2020;Lewin et al, 2009;Rowe et al, 2012). Online exercises were also found to enhance subsequent face-to-face discussions (De Leng et al, 2006).…”

“…Blended learning is now widely adopted across higher education institutions with some scholars referring to it as the "new norm" in course delivery (Adams et al, 2020;Dziuban et al, 2018;Evans et al, 2020). The term "blended learning" itself has broad and complex interpretations (Evans et al, 2020) and has always been ill-defined or defined in many ways (Graham, 2013).…”

Evaluating Item Difficulty Patterns for Assessing Student Misconceptions in Science Across Physics, Chemistry, and Biology Concepts

“…DIF analysis was performed to assess differences in item function on the basis of gender and grade on all items in test. DIF analysis investigated item responses on the basis of categorical variables for each item on assessing student misconceptions using a test (Adams et al, 2020;Boone et al, 2013). Differential item functioning analysis is categorized into three types: moderate to large (| DIF | !…”