Measures Of Student Engagement Research Articles

Exploring the use and impact of online digital resources in a mathematics module

This study examines the relationship between student engagement with digital resources and final module grade in a particular mathematics module delivered online in an Irish technological university. Measures of student engagement with the module are defined and calculated using data from virtual learning environment. These measures are analyzed to provide a description of students’ online study habits. We make an initial distinction between resources provided by the lecturer that are <i>lecture-based</i> or <i>exam-focused</i>. We further categorize student engagement with these resources as <i>active</i> or <i>passive</i> and consider these measures of student engagement in an online context. With these categories and measures in mind, we then examine the correlation between student engagement and final module grade using a multivariable linear regression model.

Digital Problem Based Learning for Facilitating the Acquisition of Collaborative Competencies

Is Networked Learning (NL) and Problem-Based Learning (PBL) the future of education to foster collaboration? Networked learning has been proposed to be combined with PBL. Both are pedagogies and philosophies influenced by traditions of open learning, radical pedagogies and humanistic educational ideas. Problem-based learning is a constructivist, student-centered, and problem-based approach used at the medical education at Aalborg University (AAU). During COVID, AAU fast-tracked the implementation of Digital PBL (DPBL) methods. Digital PBL opens new possibilities for collaborations across platforms and holds a potential to improve learning. This potential has yet to be released through systematic efforts to understand the possibilities in the context of medical education.The curriculum at the medical education at AAU is centered around the seven roles of physicians originally described in the Canadian framework, CanMEDS. Healthcare systems becomes increasingly complex, interconnected, and rely on interdisciplinary teamwork. The Collaborator role thus becomes more important than ever before. Physicians are expected to excel in clinical expertise and collaborate effectively with other healthcare professionals, patients, and families.The specific focus on collaboration is a good example of alignment between PBL-, NL pedagogy and the CanMEDS framework, and could be important to further exploration using DPBL.This study will investigate the possibilities of DPBL within the medical education at AAU by exploring and testing digitally supported pedagogical design options for facilitating the acquisition of collaborative competencies.This explorative sequential mixed-method study will explore user-needs and perspectives using DPBL in the medical education. This contextualized knowledge will inform the development of a new teaching intervention aimed at enhancing the Collaborator role. It will be evaluated using quantitative measures of student engagement, time requirements, satisfaction and self-report learning outcomes. The data will be merged with focus group interviews to gain an in-depth understanding of the quantitative results.The theoretical background will be learning design, including constructivism. This approach will be employed using the ACAD-model. The DPBL will include a digital element, the podcast media, and a pedagogical practice encouraging the medical students to engage actively in the learning process. This is facilitated by podcast production in groups.At NLC24 the findings of the user-needs and perspectives will be presented and interpreted as part of the design and frame of the podcast intervention. The intervention will take place in autumn 2024 and this can answer if NL and PBL is part of the future education to foster collaboration.

Digital Inequalities and Student Engagement in Higher Education

During the COVID-19 pandemic, education systems worldwide were forced to shut down and transition to online learning. While distance learning and digital technology offer a practical solution to mitigate the negative effects of university closure, there is also a risk of exacerbating the pre-existing digital disparities by reducing opportunities for those from less privileged backgrounds. China, as one of the first education systems to experience system-wide closure during the COVID-19 crisis, adopted emergency online learning, following a policy entitled Suspending Classes Without Stopping Learning. In the past three years, we have witnessed a growing number of studies on students’ online learning experiences. However, most of these studies have focused on a behavioural perspective which centres on student behaviour and effective institutional practices, thereby neglecting the exploration of broader sociocultural contexts that may influence student experiences. Moreover, the majority of empirical studies have laid particular emphasis on quantitative measures of student engagement through large-scale surveys, while very limited studies have explored in-depth factors that influence student engagement. This short paper offers a brief overview of an ongoing research project that focuses on exploring the day-to-day digital practice of students in two different types of universities in China. Adopting a digital ethnographic approach including visual methods, online observations, semi-structured interviews and comparative ethnographic analysis, this study aims to provide a detailed qualitative understanding of student experiences working with digital technologies in both research-oriented universities and teaching-oriented universities. Throughout the theoretical discussion of different approaches to digital inequalities, this paper hopes to stimulate thinking about the forms of the digital divide that might exist in higher education and ultimately contribute to both academic and policy debates on the subject. By exploring the different meanings of student engagement, this paper exhibits some of the challenges and issues relating to conceptualising and measuring student engagement in the digital age. It is hoped that this paper will bring insights into reframing and conceptualising student engagement from a socio-material perspective that moves away from the dominance of behavioural and quantitative studies. The finding of this study will contribute to providing a nuanced understanding of the relationship between initial socioeconomic inequalities, differences in student engagement and resulting inequalities in post-higher education, which will potentially inform future educational practitioners and scholars alike in developing effective strategies to enhance student learning experiences in the digital sphere.

AI ChatGPT and student engagement: Unraveling dimensions through PRISMA analysis for enhanced learning experiences

This PRISMA-based literature review aims to assess and analyze the measurement of student engagement dimensions within AI ChatGPT interactions. The central question is how to effectively evaluate these dimensions using established methods and leverage insights to enhance AI ChatGPT’s capacity to foster student engagement. The systematic review of PRISMA methodology identifies 16 relevant peer-reviewed research. All relevant and eligible research according to PRISMA methodology are analyzed to comprehend the intricacies of student engagement in AI ChatGPT interactions. The synthesis of these findings unveils the current state of knowledge on AI ChatGPT’s influence on student engagement and uncovers opportunities for future research. This review underscores AI ChatGPT’s potential as an educational tool, offering personalized experiences that bolster student engagement and learning outcomes. The systematic review established that, even though using ChatGPT has many advantages such as enhancing student engagement and academic involvement and supporting inquiry-based learning. However, there are some negative aspects such as lacking empathy and human emotions, limited contextual understanding, increased technology dependence and possibility of Inaccurate or Biased Information. In summary, this PRISMA-based review contributes to understanding the measurement of student engagement within AI ChatGPT. It identifies best practices, laying the foundation for further research and development. By optimizing AI ChatGPT’s effectiveness, educators and developers can craft more engaging and tailored learning experiences, ultimately enhancing educational outcomes.

Measurement of Student Engagement in a Generic and Online Learning Management System-Based Environment

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.

Bridging Theory and Measurement of Student Engagement

Learner engagement is well-established as critical for learning online. Professional development for online instructors emphasizes techniques for engaging students, and learning technology products tout features intended to promote engagement (e.g., adaptive content, video, gamification). But the influence of particular instructor practices and of particular learning technology features on theory-based aspects of student engagement is infrequently tested empirically, and even more rarely with Black, Latine, and low-income students, who are more likely to face barriers to learning online. This paper first provides a research-based theoretical model of affective engagement developed in conjunction with ongoing studies of blended learning implementations of courseware designed to enhance learning and engagement among historically and systemically marginalized students. Next, the paper describes development of survey-based measures of four components of affective engagement and the use of responses from over 850 students in introductory statistics courses to evaluate the reliability and factor structure of those measures. We conclude with implications for use of the engagement measures in future improvement-oriented research and practice.

Unravelling the relationship between student engagement and learning outcomes in emergency online learning: a synthesis of quantitative and qualitative results

Adopting a mixed methods approach, this study examined the relationships between undergraduate students’ motivation, engagement and learning outcomes during the COVID-19 pandemic. An online questionnaire survey was administered to collect quantitative and qualitative data. A sample of 10,060 undergraduates from 23 universities in China participated in the survey. The results of quantitative analyses largely confirmed the hypothesised relationships between students’ motivation, engagement and the two learning outcome indicators (i.e. mastery of generic skills and overall satisfaction). The qualitative analyses not only supported the quantitative findings, but also identified four types of learning outcomes of online learning emerging from the data. The results indicated that emergent online learning had a favourable influence on students’ learning strategies, but had mixed or negative effects on their learning effectiveness, attitudes and emotions. The qualitative results revealed eight major factors that facilitated or hindered students’ engagement in online learning during the pandemic. These findings contribute to the conceptualisation and measurement of student engagement in online learning, and emphasise the need to conduct mixed methods research in different learning contexts. The implications for improving online learning and teaching in higher education are discussed.

The student engagement scale: evidence of psychometric validity in Chinese and English language subjects from grade 4 to grade 6 in China

The three-dimensional (i.e. affective, behavioural, and cognitive) conceptualisation of student engagement has been the prevalent framework for understanding student engagement, but most existing research has focussed on general, rather than subject-specific, student engagement. The present study tested the psychometric properties of a measure of student engagement for two language-relevant subject areas (Chinese and English) developed from general student engagement measures using a structural equation modelling approach. The sample consisted of 778 students (M = 10.43 years, SD = 0.99) from grades 4 to 6 in Shanghai, China. This study adapted the general student engagement scales to develop measures of student engagement in the subject areas of Chinese and English language for Chinese students within the three-dimensional engagement framework. Confirmatory factor analysis (CFA) supported the three-factor model, showing adequate fit for each subject area. In addition, the model showed configural, metric, and scalar invariance across both gender and grade groups. There were also some latent mean differences in the subject-specific student engagement constructs between gender and age groups. These results indicate that the student engagement measure for the two subject areas has acceptable psychometric properties.

Cross-Cultural Validation of the Student Engagement Instrument for Chilean Students

Student engagement is associated with various aspects of students’ school experiences, including student achievement, high school completion, and post-secondary success. As measurement of student engagement has grown in countries around the world, few studies have been conducted in South America. This study examined a translated version of the Student Engagement Instrument, widely used in the U.S. and other countries, in a study of 2337 adolescents in Chile. Consistent with prior research, confirmatory factor analyses revealed a six-factor solution as the best fit for the data. However, fewer items were retained than on the studies of the SEI with students in the U.S. The Future Goals and Aspirations and Extrinsic motivation subscales were associated, in expected directions, with achievement 1 year later.

Individual and Group-wise Classroom Seating Experience

Seating location in the classroom can affect student engagement, attention and academic performance by providing better visibility, improved movement, and participation in discussions. Existing studies typically explore how traditional seating arrangements (e.g. grouped tables or traditional rows) influence students' perceived engagement, without considering group seating behaviours under more flexible seating arrangements. Furthermore, survey-based measures of student engagement are prone to subjectivity and various response bias. Therefore, in this research, we investigate how individual and group-wise classroom seating experiences affect student engagement using wearable physiological sensors. We conducted a field study at a high school and collected survey and wearable data from 23 students in 10 courses over four weeks. We aim to answer the following research questions: 1. How does the seating proximity between students relate to their perceived learning engagement? 2. How do students' group seating behaviours relate to their physiologically-based measures of engagement (i.e. physiological arousal and physiological synchrony)? Experiment results indicate that the individual and group-wise classroom seating experience is associated with perceived student engagement and physiologically-based engagement measured from electrodermal activity. We also find that students who sit close together are more likely to have similar learning engagement and tend to have high physiological synchrony. This research opens up opportunities to explore the implications of flexible seating arrangements and has great potential to maximize student engagement by suggesting intelligent seating choices in the future.

A mixed blessing: student engagement in emergency online learning during COVID-19 in China

With a sample of 4,646 undergraduate students from four universities in China, this study examined the psychometric qualities of a newly-adapted measurement, namely, the Online Motivation and Engagement Scale for university and college students, and investigated the characteristics of and differences in Chinese students’ motivation and engagement in emergent online learning during the COVID-19 pandemic. The results supported the reliability and construct validity of the measurement, and identified four types of learners with distinctive features of student engagement. The research revealed a complex picture with promising and worrying messages about student engagement in emergency online learning during the pandemic. These findings contribute to the conceptualisation and measurement of student engagement in online learning, and provide insights for improving online learning and teaching during and beyond the pandemic.

Student engagement in undergraduate medical education: A scoping review.

Student engagement is defined as behavioural, cognitive and emotional aspects of students' academic experience in teaching, learning and research through interacting with other students, faculty and community. Despite the growing interest in the field of student engagement, medical education research in this area is still fragmented. This scoping review aims to contribute to the understanding of measurements, drivers and outcomes of medical student engagement. The authors searched MEDLINE, PubMed, ProQuest, SCOPUS, ERIC, Science Direct and EBESCO for English articles published from 1990 until October 2021. In addition, we hand-searched key medical education journals and references in recently published articles. Using specific selection criteria, two authors independently reviewed the articles for eligibility, followed by data extraction using both quantitative and qualitative analysis. Of the 2136 retrieved articles, 51 studies were selected for the review, and 94% of them were published in the past 8years. The prevailing measures of student engagement failed to cover the multidimensionality of the construct with more focus on the behavioural dimension. Quantitative methods represented two thirds of the studies with a higher frequency of cross-sectional designs and using self-reports. The identified drivers of medical students' engagement are directed mainly to modifying the context of the learning environment. These factors increased student engagement by fostering relevance of learning, positive student relationships with peers and faculty, and enhancing student agency, and sense of competence. Cognitive engagement appears to be a positive predictor of academic achievement, but the relationship with other dimensions of engagement is controversial. Student engagement in undergraduate medical education is an important, yet under-researched construct. The research that does exist suggests engagement to be malleable, something that can be modified by different types of interventions taking into consideration the context of education and practice. Further research is required, however, to address the gaps identified in this review.

Development and Evaluation of a Survey to Measure Student Engagement at the Activity Level in General Chemistry

Student engagement is an important consideration when incorporating active learning activities into a classroom. To facilitate the large-scale assessment of students’ engagement in activities, a survey measure must first be developed and evaluated. Therefore, the goal of this study was to create a self-report measure of student engagement for use with active learning activities in general chemistry classes. The Activity Engagement Survey (AcES) was modified from an existing survey of engagement of middle and high school science students that contained behavioral, cognitive, emotional, and social engagement items. Multiple rounds of response process interviews and factor analyses were used to modify the measure and provide evidence of validity for the data collected. The results provided support for the presence of a bifactor model, where an overall general engagement factor and the individual dimensions of engagement were simultaneously modeled. Additionally, support was found for combining behavioral and cognitive components into a single factor due to a large overlap in students’ perceptions between the constructs.

Development of a student engagement score for online undergraduate engineering courses using learning management system interaction data

AbstractAlthough researchers agree that student engagement in online courses is a function of time dedicated to course‐related activities, there is little consensus about the best way to quantify the construct. This study introduces a measure for undergraduate engineering students' engagement in online courses using their interactions with their online course learning management system (LMS). Data from 81 courses offered by three fully online, undergraduate engineering degree programs generated a total of 3848 unique student–course combinations (approximately 2.7 million rows of LMS interaction data), to which we applied a five‐step process to calculate a single score representing student LMS engagement. First, we converted the students' LMS interaction data into a set of natural features representing the time they spent per 3‐day period on various course elements, such as quizzes, assignments, discussion forums, and so forth, and how these times changed across the duration of the course. We then used the natural features to derive 216 relative features describing deviations from typical interaction patterns among students in the same course. Next, we conducted association rule mining on a training portion of the data set to generate rules separately describing the behavior of students who completed the course (completers) and those who chose to drop early (leavers). The rules generated were applied to students from the testing portion of the data set to compute the percentage of unique rules met by completers and leavers. Finally, the mathematical difference between the percentages of completer and leaver rules met by each student was found to be the best measure of student engagement.

Do students with immigrant and native parents perceive themselves as equally engaged in school during adolescence?

Student engagement in school needs to be considered when comparing immigrant and native students, particularly at a time of increasing migratory movements throughout the world. Differences in cognitive, affective, behavioral, and agentic student engagement dimensions were examined for students with immigrant and native parents, and for early and middle adolescence. A four-dimensional measure of student engagement was completed by 643 students (52.7% women). Results indicated that: students with native parents present higher cognitive and agentic engagement than students with immigrant parents; early adolescents are more cognitively engaged than middle adolescents; early adolescents with native parents present higher cognitive engagement than early adolescents with immigrant parents and middle adolescents. These results contribute to knowledge advancement, enhancing the understanding of student engagement with immigrant and native parents during early and middle adolescence, which might stimulate additional research moving towards a more inclusive school. Based on the findings and conclusions from this study, possibilities for future research and political-educational recommendations are presented.

Enhancing Student Engagement and Self-Evaluation Using Student Response Systems

Whilst previous studies are broadly in agreement on the effectiveness of student response systems (hereafter SRSs) in enhancing student engagement, there are gaps in the literature relating to study design and outcomes assessed. This study offers enhancements to study design. First, by collecting baseline data, engagement levels can be conditioned and changes in engagement attributable to the SRS detected. Second, it is one of the few studies that employs a comprehensive measure of student engagement. Third, analysis occurs at student level rather than class level. The study finds increased positive perceptions towards self￾evaluation (both self and relative assessment) and ability to express opinion, in addition to strong student positivity towards the SRS.

Understanding afterschool engagement: Investigating developmental outcomes for adolescents.

Though student engagement is hypothesized to be a factor in explaining student level differences in afterschool programs, the measurement of student engagement in this context is inconsistent, and findings from the small number of studies about how engagement impacts developmental and academic outcomes are mixed. In this study, we tested the factor structure of Wang and colleagues' school engagement scale with a sample of middle school students (N = 197) who attended an afterschool program in an urban setting. Results suggest that a bifactor model of engagement best fits the data, meaning that engagement consists of four specific factors (affective, behavioral, cognitive, social) and a global factor. We then used structural equation modeling to examine the relationship between engagement, academic outcomes, and positive youth development (PYD). Results also showed positive associations with student mathematics achievement and PYD, but no significant associations were found between engagement and English achievement. This study provides a theoretically aligned way to measure engagement and evidence to support engagement as a key factor in predicting youth outcomes in an out-of-school context.

A Multicomponent mHealth-Based Intervention (SWAP IT) to Decrease the Consumption of Discretionary Foods Packed in School Lunchboxes: Type I Effectiveness-Implementation Hybrid Cluster Randomized Controlled Trial.

BackgroundThere is significant opportunity to improve the nutritional quality of foods packed in children’s school lunchboxes. Interventions that are effective and scalable targeting the school and home environment are therefore warranted.ObjectiveThis study aimed to assess the effectiveness of a multicomponent, mobile health–based intervention, SWAP IT, in reducing the energy contribution of discretionary (ie, less healthy) foods and drinks packed for children to consume at school.MethodsA type I effectiveness–implementation hybrid cluster randomized controlled trial was conducted in 32 primary schools located across 3 local health districts in New South Wales, Australia, to compare the effects of a 6-month intervention targeting foods packed in children’s lunchboxes with those of a usual care control. Primary schools were eligible if they were not participating in other nutrition studies and used the required school communication app. The Behaviour Change Wheel was used to co-design the multicomponent SWAP IT intervention, which consisted of the following: school lunchbox nutrition guidelines, curriculum lessons, information pushed to parents digitally via an existing school communication app, and additional parent resources to address common barriers to packing healthy lunchboxes. The primary outcome, mean energy (kilojoules) content of discretionary lunchbox foods and drinks packed in lunchboxes, was measured via observation using a validated school food checklist at baseline (May 2019) and at 6-month follow-up (October 2019). Additional secondary outcomes included mean lunchbox energy from discretionary foods consumed, mean total lunchbox energy packed and consumed, mean energy content of core lunchbox foods packed and consumed, and percentage of lunchbox energy from discretionary and core foods, all of which were also measured via observation using a validated school food checklist. Measures of school engagement, consumption of discretionary foods outside of school hours, and lunchbox cost were also collected at baseline and at 6-month follow-up. Data were analyzed via hierarchical linear regression models, with controlling for clustering, socioeconomic status, and remoteness.ResultsA total of 3022 (3022/7212, 41.90%) students consented to participate in the evaluation (mean age 7.8 years; 1487/3022, 49.22% girls). There were significant reductions between the intervention and control groups in the primary trial outcome, mean energy (kilojoules) content of discretionary foods packed in lunchboxes (–117.26 kJ; 95% CI –195.59 to –39.83; P=.003). Relative to the control, the intervention also significantly reduced secondary outcomes regarding the mean total lunchbox energy (kilojoules) packed (–88.38 kJ; 95% CI –172.84 to –3.92; P=.04) and consumed (–117.17 kJ; 95% CI –233.72 to –0.62; P=.05). There was no significant difference between groups in measures of student engagement, consumption of discretionary foods outside of school hours, or cost of foods packed in children’s lunchboxes.ConclusionsThe SWAP IT intervention was effective in reducing the energy content of foods packed for and consumed by primary school–aged children at school. Dissemination of the SWAP IT program at a population level has the potential to influence a significant proportion of primary school–aged children, impacting weight status and associated health care costs.Trial RegistrationAustralian Clinical Trials Registry ACTRN12618001731280; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=376191&isReview=trueInternational Registered Report Identifier (IRRID)RR2-10.1186/s12889-019-7725-x

Student behavior analysis to measure engagement levels in online learning environments.

After the COVID-19 pandemic, no one refutes the importance of smart online learning systems in the educational process. Measuring student engagement is a crucial step towards smart online learning systems. A smart online learning system can automatically adapt to learners’ emotions and provide feedback about their motivations. In the last few decades, online learning environments have generated tremendous interest among researchers in computer-based education. The challenge that researchers face is how to measure student engagement based on their emotions. There has been an increasing interest towards computer vision and camera-based solutions as technology that overcomes the limits of both human observations and expensive equipment used to measure student engagement. Several solutions have been proposed to measure student engagement, but few are behavior-based approaches. In response to these issues, in this paper, we propose a new automatic multimodal approach to measure student engagement levels in real time. Thus, to offer robust and accurate student engagement measures, we combine and analyze three modalities representing students’ behaviors: emotions from facial expressions, keyboard keystrokes, and mouse movements. Such a solution operates in real time while providing the exact level of engagement and using the least expensive equipment possible. We validate the proposed multimodal approach through three main experiments, namely single, dual, and multimodal research modalities in novel engagement datasets. In fact, we build new and realistic student engagement datasets to validate our contributions. We record the highest accuracy value (95.23%) for the multimodal approach and the lowest value of “0.04” for mean square error (MSE).

Biosensors Show Promise as a Measure of Student Engagement in a Large Introductory Biology Course.

This study measured student engagement in real time through the use of skin biosensors, specifically galvanic skin response (GSR), in a large undergraduate lecture classroom. The study was conducted during an intervention in an introductory-level biology course (N = 420) in which one section of the course was taught with active-learning approaches and the other with traditional didactic teaching. GSR results were aligned and correlated with the Classroom Observation Protocol for Undergraduate STEM, or COPUS, and student self-reflections on their own engagement. Results showed that the active-learning section spent more time working in groups, resulting in GSR measures that trended higher and self-reported engagement, while showing indications of higher content learning gains compared with the traditional lecture section. Comparisons between COPUS scores and GSR readings indicate that engagement increased during group work and decreased during listening activities. Throughout a class period, GSR activity of the active-learning group showed increased trends compared with baseline measures, while the traditional lecture group showed decreased trends. Results indicate that GSR is a promising measure of real-time student engagement in the undergraduate classroom, bringing a new technique to discipline-based education researchers who aim to better measure student engagement; however, some limitations exist for broad-scale implementation.