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Experiencing the Educational Interface: Understanding Student Engagement. STARS Conference, Adelaide, Australia, 2017. https://unistars.org/papers/STARS2017/P04.pdf

This study describes the development and validation of the Higher Education Student Engagement Scale (HESES). The psychometric evaluations of the scale included: (i) factor structure, (ii) internal consistency, and (iii) criterion validity. The HESES was developed based on our proposed five-factor model of student engagement, which was evolved from Finn and Zimmer's (In: Christenson SL, Reschly AL, Wylie C (eds) Handbook of research on student engagement. Springer, New York, 2012) student engagement model taken into account the distinctive characteristics in higher education. The five main facets of student engagement include: (1) academic engagement, (2) cognitive engagement, (3) social engagement with peers, (4) social engagement with teachers, and (5) affective engagement. The HESES was developed from the 61-item First Year Engagement Scales (FYES). For brevity, it was trimmed into a 28-item scale having regard to the content validity, factor loadings and error variances of the items. The CFA results supported the correlated five-dimensional model with all the dimensions showing high internal consistency based on Cronbach's alpha coefficients. A multi-group CFA also rendered the structure as gender invariant. Its criterion validity was evidenced by its correlations with different student learning outcomes and more importantly, its predictive power in explaining variances of GPA (15%) and satisfaction of the university experience (29%). Different from the dominant behavioral perspective of student engagement in higher education, the HESES is based on a psychological perspective, streamlining student engagement as students' level of involvement in the learning process and a multi-faceted construct with academic, cognitive, social and affective dimensions. The implications and merits of the HESES are discussed.

The present study examined the relationships between student engagement, represented by two versions of the National Survey of Student Engagement (NSSE) and self-reported gains in learning. The study drew on institutional-level data from participating institutions in 2011 and 2013. The objective of the research was to compare evidence of convergence and discrimination for the two versions of NSSE using canonical correlation analysis. Results indicated that both versions of NSSE provided clear evidence of convergence in that student engagement measures were significantly and positively related to perceived gains in learning. However, only the most recent version of NSSE provided strong evidence of discrimination (i.e., differential relationships between engagement measures and self-reported learning outcomes). Thus, the revised NSSE appears to offer substantial advantages for institutions interested in more nuanced understandings of the relationships between student engagement and perceived learning outcomes. Implications for educators, with goals of enhancing student learning, and for researchers, who often compare complex sets of data, are included.

Student engagement is a multifaceted construct having different dimensions: cognitive, behavioural, and emotional. Despite its centrality in learning and learning outcomes, student engagement has proven difficult to measure. Furthermore, it is under researched in undergraduate sciences, including physics. The aim of this paper is to present the development, validation, and evaluation of a survey which measures student engagement in physics laboratory learning; the Science Student Laboratory Engagement Questionnaire (SSLEQ). The survey measures undergraduate students’ cognitive, behavioural, and emotional engagement while doing experiments. Items from ASLE (ASELL Student Learning Experience) and AEQ (Achievement Emotions Questionnaire)-Physics Prac were adapted in developing this survey. The items for cognitive engagement are about motivators underpinning understanding of content and development of skills. The items for behavioural engagement query the resources provided such as experimental lab notes and demonstrators’ help. For emotional engagement, items explored positive and negative emotions. Confirmatory factor analysis and descriptive statistics conducted with a sample of 308 first year physics students confirm the reliability and internal validity of the survey for the purposes. This survey was evaluated with the first year physics students to compare engagement with students who experienced a face to face laboratory session before moving to online and students who experienced only online laboratory sessions. This survey can now be used in other contexts providing academics with measures of three types of engagement for use in science courses to positively influence students’ engagement with laboratory exercises.

Previous studies have proposed many indicators to assess the effect of student engagement in learning and academic achievement but have not yet been clearly articulated. In addition, while student engagement tracking systems have been designed, they rely on the log data but not on performance data. This paper presents results of a non-machine learning model developed using ongoing formative assessment scores as indicators of student engagement. Visualisation of the classification tree results is employed as student engagement indicators for instructors to observe and intervene with students. The results of this study showed that ongoing assessment is related to student engagement and subsequent final programming exam performance and possible to identify students at-risk of failing the final exam. Finally, our study identified students impacted by the Covid-19 pandemic. These were students who attended the final programming exam in the semester 2019-2020 and who scored well in formative assessments. Based on these results we present a simple student engagement indicator and its potential application as a student progress monitor for early identification of students at risk.

Use of technology on campuses of higher education has changed how students are engaged in the process of learning. It also has brought lot of asynchrony to the definition of class room teaching, active learning, student-staff interactions, and dealing with various academic challenges. The paper presents a study conducted to measure student engagement in a generic and online learning management system-based teaching learning environment. The paper presents threefold results. The first one is on identification of student engagement styles. The styles identified can further be used to design, develop, and implement most student engaging policies on campus which are beneficial to all the stakeholders. Second, the central point of the study is the student and her/his engagement with the learning process. The paper presents a student engagement report card to individual students for their analysis. Informing and involving students to know about their engagement report card would be beneficial. The third is feedback on a trail left by students' logs on the learning management system that can help the teachers to plan the teaching methodology. The methodology used was based on the data collected by the students of the institute/university. A student engagement questionnaire was used to measure student engagement in both generic and online learning environments. A cluster analysis was conducted on the data collected to identify the student engagement styles. A subcategory analysis was reported as a student engagement report card. The student-logged data on the institute learning management system was used to present the third analysis.

This research examined the relationships among students' academic majors, levels of engagement, and learning outcomes within the context of Holland's person— environment theory of vocational and educational behavior. The study focused on the role of student engagement as a mediating agent in the relationships between academic majors and student learning. Drawing on data from a stratified random sample of 20,000 seniors who participated in the 2008 National Survey of Student Engagement, results revealed that students' academic majors were significantly related to levels of engagement and learning outcomes. Student engagement was also significantly related to learning outcomes. Students' academic majors generally were not indirectly related to learning outcomes through levels of engagement. An important exception to this result was found for students in Enterprising environments where indirect relationships among Enterprising disciplines and Enterprising learning outcomes were positive, statistically significant, and substantially larger than the direct relationship.

Purpose - Entrepreneurship education particularly requires student engagement because of the complexity of the entrepreneurship process. The purpose of this paper is to describe how an established measure of engagement can be used to identify relevant teaching methods that could be used to engage any group of entrepreneurship students.Design methodology approach - The Australasian Survey of Student Engagement (AUSSE) instrument was used to provide 47 well established engagement criteria. The results from 393 students (33 per cent response rate), and the identification by immersed experts of the criteria that were present in each of six teaching methods, made it possible to calculate a weighted score of engagement contribution for each teaching method.Findings - This method described in this paper identified, for undergraduate entrepreneurship students, the most engaging teaching methods as well as the least engaging. This approach found that from amongst the particular range of teaching methods in the courses in this case study, poster reports was the most engaging, followed by a team-based learning method. This approach also identified one teaching method that was not engaging, suggesting it could be discontinued.Practical implications - These results give entrepreneurship educators with access to engagement data collected by the National Study of Student Engagement (NSSE), or the equivalent AUSSE study, a practical method for assessing and identifying teaching methods for student engagement for their particular profile of students, and in their particular teaching situation.Originality value - The application of established measures of engagement is novel and provides insights into specific teaching methods for enhancing the engagement of particular groups of students at the course level. It is a method that could be applied in fields other than entrepreneurship education where NSSE or AUSSE data is available.

Student learning and development are the core business of the academy, yet until recently Australian and New Zealand universities lacked data on students' engagement in effective educational practices. This paper reports the foundations and development of the Australasian Survey of Student Engagement (AUSSE)-the largest educationally focused cross-institutional collection from current students in Australasia. Results from the 2008 AUSSE are analyzed to elucidate the focus and significance of the collection. A review is undertaken of the AUSSE's approach to stimulating each institution's continuous improvement. The analysis is expanded, by way of conclusion, to consider the role of the collection as a general agent for encouraging the expansion of evidence-based quality management in higher education. (HRK / Abstract übernommen).

Issues relating to student engagement with their studies have become high on the agendas of higher education institutions both locally and globally. This paper reports on a research aiming to investigate the factors that determine student engagement in the different degree courses within a sample of 50 third year undergraduate EFL students in the Department of English, University of Algiers 2 during the first semester of the academic year 2024/2025. Data for the study were collected using a mixed questionnaire and follow-up interviews. The findings have shown that course credit, interest in course content, attendance policy, career pressure, campus environment, use of technological tools, classroom tasks, perceived usefulness of the course, assessment mode, students’ rapport with the teacher, along with classroom interaction and intrinsic motivation are factors that influence student engagement. Although these factors were found to affect student engagement to greater or lesser extent, the teacher’s instructional style was found to be the most determining factor. Based on the findings of this study, some suggestions are made to students, teachers, and policymakers in order to help students engage more deeply with their courses. It is recommended that future research examines the impact of such factors as intrinsic motivation, as well as interaction on student course engagement at university in more detail in order to advance related scholarship and practice in this area.