Engaging Young Learners: Instructional Models and Engagement in Musical Play

The degree of learning engagement is a criterion for measuring whether the learning process of college students is effective and an important indicator for evaluating the quality of higher education. Currently, there is a lack of survey research focusing on the current situation of English learning engagement among non-English major college students. This study aims to explore the English learning engagement of non-English major college students by using the method of questionnaire survey. A questionnaire survey was conducted among 157 non-English major undergraduates in a certain university, including 59 male students and 98 female students. The survey results are as follows: (1) The levels of behavioral engagement, emotional engagement, and cognitive engagement in English learning among non-English major undergraduates are at a medium level. (2) The levels of behavioral and emotional engagement of female students are significantly higher than those of male students. (3) The levels of emotional and cognitive engagement of sophomores are significantly higher than those of freshmen. (4) The levels of behavioral, emotional, and cognitive engagement of liberal arts students are significantly higher than those of science students. These findings provide valuable insights into the English learning engagement of non - English major college students. And some useful implications are provided for teachers, universities, and students themselves to improve the overall quality of English learning engagement among this group of students. Future research could further explore the underlying reasons for these differences and seek more effective ways to enhance the English learning engagement and outcomes of non - English major college students.

With the proliferation of digital mental health interventions (DMHIs) guided by relational agents, little is known about the behavioral, cognitive, and affective engagement components associated with symptom improvement over time. Obtaining a better understanding could lend clues about recommended use for particular subgroups of the population, the potency of different intervention components, and the mechanisms underlying the intervention's success. This exploratory study applied clustering techniques to a range of engagement indicators, which were mapped to the intervention's active components and the connect, attend, participate, and enact (CAPE) model, to examine the prevalence and characterization of each identified cluster among users of a relational agent-guided DMHI. We invited adults aged 18 years or older who were interested in using digital support to help with mood management or stress reduction through social media to participate in an 8-week DMHI guided by a natural language processing-supported relational agent, Woebot. Users completed assessments of affective and cognitive engagement, working alliance as measured by goal and task working alliance subscale scores, and enactment (ie, application of therapeutic recommendations in real-world settings). The app passively collected data on behavioral engagement (ie, utilization). We applied agglomerative hierarchical clustering analysis to the engagement indicators to identify the number of clusters that provided the best fit to the data collected, characterized the clusters, and then examined associations with baseline demographic and clinical characteristics as well as mental health outcomes at week 8. Exploratory analyses (n=202) supported 3 clusters: (1) "typical utilizers" (n=81, 40%), who had intermediate levels of behavioral engagement; (2) "early utilizers" (n=58, 29%), who had the nominally highest levels of behavioral engagement in week 1; and (3) "efficient engagers" (n=63, 31%), who had significantly higher levels of affective and cognitive engagement but the lowest level of behavioral engagement. With respect to mental health baseline and outcome measures, efficient engagers had significantly higher levels of baseline resilience (P<.001) and greater declines in depressive symptoms (P=.01) and stress (P=.01) from baseline to week 8 compared to typical utilizers. Significant differences across clusters were found by age, gender identity, race and ethnicity, sexual orientation, education, and insurance coverage. The main analytic findings remained robust in sensitivity analyses. There were 3 distinct engagement clusters found, each with distinct baseline demographic and clinical traits and mental health outcomes. Additional research is needed to inform fine-grained recommendations regarding optimal engagement and to determine the best sequence of particular intervention components with known potency. The findings represent an important first step in disentangling the complex interplay between different affective, cognitive, and behavioral engagement indicators and outcomes associated with use of a DMHI incorporating a natural language processing-supported relational agent. ClinicalTrials.gov NCT05672745; https://classic.clinicaltrials.gov/ct2/show/NCT05672745.

The progress of artificial intelligence (AI) has sparked significant research interest in its application in education and students’ perceptions of and response to this technology. This multiple-case study explores three Chinese university students’ (representing high-, intermediate-, and low-level English proficiency) engagement with AI-guided chatbot feedback in English writing learning. Data sources include chat records, written drafts and semi-structured interviews. The study identifies two sub-dimensions, interaction and revision, to characterize students’ behavioral, cognitive, and emotional engagement with AI-guided chatbot feedback. The findings demonstrate that all students exhibited high levels of behavioral engagement during interactions, while only intermediate- and high-level students demonstrated significant cognitive engagement during interaction. Besides, the high-level student displayed higher levels of behavioral and cognitive engagement in the revision process compared to her counterparts. Finally, students’ emotional engagement was intricate in both interaction and revision process, exhibiting various approbations and concerns towards the application of AI-guided chatbot in writing learning. These insights can inform the effective implementation of AI-guided chatbot in providing feedback for second language writing instruction.

Available evidence suggests that learners’ level of emotional intelligence and academic buoyancy are associated with components of behavioural and emotional engagement. Recent work has provided preliminary evidence that the relationship between emotional intelligence and student engagement is mediated by academic buoyancy. Therefore, the current study was designed to determine if the association between emotional intelligence, behavioural engagement, emotional engagement, behavioural disaffection, and emotional disaffection is mediated by academic buoyancy. A sample of 253 undergraduate and graduate students completed self-report measures of the primary constructs of interest. Results of an a priori path analysis indicated that emotional intelligence had a significant direct effect on behavioural and emotional engagement and behavioural and emotional disaffection. Our results also revealed academic buoyancy shared a direct relationship with behavioural and emotional engagement and emotional disaffection. Critically, our results provided additional evidence that the relationship between components of student engagement – behavioural engagement, emotional engagement, and emotional disaffection – was partially mediated by academic buoyancy. Discussion concerns the potential benefits of implementing interventions designed to enhance emotional intelligence in an effort to increase learners coping potential, engagement, and overall academic success.

The most urgent need of higher education is now to cultivate high-quality talent. The inexhaustible impetus for the connotative and high-quality development of higher education includes whether distance education can improve its quality and efficiency. As an important indicator of the quality of online learning of college students, the level of learning engagement has gradually gained the attention and research of experts and scholars. This study focuses on synchronous online learning in online learning, which can guide teachers to design better online courses. This study analyzes the current situation of the online learning engagement level of college students from a micro perspective, which helps us to understand the role of college students' learning engagement in distance learning to improve the professional development ability of college students and promote the quality of education in higher education institutions. Based on student participation theory and learning engagement theory, this study uses stratified sampling and random sampling to select 142 college students in a university in western China as the research subjects and adopts quantitative analysis as the main method and a combination of qualitative and quantitative analysis to explore the online learning engagement of college students in a university in western China. The results showed that the overall online learning commitment of college students in a university in western China was moderate. Specifically, the level of cognitive engagement in the online classroom was moderate, the level of emotional engagement in the online classroom was good, and the level of behavioral engagement in the online classroom was poor. By describing the current situation, we can see that there are some problems in college students' online learning engagement. Based on the theory of learning engagement, specific research data and the results of semi-structured interviews, we propose some suggestions to improve the online learning engagement of college students in a university in western China from three aspects: cognitive engagement, behavioral engagement, and emotional engagement.

Storytelling activities delivered by social robots have not been adequately studied in the existing literature. Prior work has mainly investigated the use of social robots in telling stories to young children. Our study examined the effects of both storytelling and story co-telling facilitated by a social robot on children’s learning engagement and story comprehension, comparing to the same activities facilitated by a human and a tablet. Adopting an experimental design, the levels of emotional, behavioral and cognitive engagement and story comprehension of 77 children (aged 5–7) who participated in two storytelling activities (listening to a story and co-telling a story) facilitated by either a robot, a tablet, or a human were measured. Changes in behavioral engagement between the two learning activities were also examined. Our results showed that the levels of behavioral and cognitive engagement in the social robot condition were comparable to the human condition, and better than the tablet condition. Interestingly, behavioral engagement was maintained from listening to a story to co-telling the story in the social robot condition and the human condition but not the tablet condition. However, no significant differences were found in emotional engagement and story comprehension across conditions. The findings suggest that social robots are effective educational tools to engage young children in storytelling activities.

This study explores the nexus between work-life balance (WLB) strategies and employees’ engagement (EE) within the food and beverage (F&amp;B) industry. Employing a quasi-experimental design, data was gathered from 165 employees across selected F&amp;B organizations using a closed-ended Likert-type scale questionnaire. Data analysis via Pearson’s Product Moment correlation (PPMC) statistical technique revealed a positive and significant relationship between the dimensions of work-life balance (WLB) strategies and measures of employees’ engagement (EE) within the food and beverage (F&amp;B) industry. Specifically, the results indicate a robust positive and significant correlation between Work interference with personal life (WIPL) and the measures of employees’ engagement: employees’ emotional engagement (EEE) and employees’ behavioral engagement (EBE), with values ranging from 0.894 to 0.881 respectively. Additionally, personal life interference with work (PLIW) demonstrates a notable positive correlation with the measures of employees’ engagement, attributing to 72.5% to 83.5% of emotional and behavioral engagement, respectively. Furthermore, work enhancement of personal life (WEPL) initiatives and personal life enhancement of work (PLEW) initiatives exhibited very strong positive associations with the measures of employees’ engagement, explaining up to 74% to 85% of emotional and behavioral engagement, respectively. These findings corroborate prior research, highlighting the significance of addressing Work-Life Balance issues to bolster employees’ engagement levels. Practically, the study underscores the importance for managers in the Food and Beverage to prioritize strategies that mitigate work-life interference, such as flexible scheduling and family-friendly policies, to foster higher EE levels. Tailored initiatives and training programs should be implemented to address specific WLB aspects identified within organizations, while fostering open communication channels to identify areas for improvement. By prioritizing WLB and supporting employee well-being, managers can cultivate a more engaged and productive workforce, ultimately contributing to organizational success. Other theoretical and practical implications for promoting WLB and fostering employees’ engagement in the Nigerian workplace are also discussed.

Developing adequate English as a Foreign Language (EFL) academic writing skills is of paramount importance for students’ success in higher education in Oman. The traditional teaching approaches adopted in writing courses often lead to students’ disengagement, however. Although several studies have examined students and teachers’ perceptions of flipped instruction in various EFL courses, no study has examined the impact of flipping on students’ engagement in writing courses. This practice-based research project, where the instructor was the researcher, explored the impact of flipped teaching on 57 General Foundation Program (GFP) EFL learners’ behavioural, cognitive, emotional and agentic engagement in academic writing in a higher education institution in Oman, and the variations that exist in students’ engagement according to gender, age, English language proficiency and technology skills. The study adopted a mixed-methods design and used a student engagement questionnaire, focus group interviews and participant observations to collect data. Descriptive and inferential statistics and deductive and inductive analytical procedures were used to analyse the quantitative and qualitative data respectively. The study presents new practicable knowledge about the implementation and implications of flipped instruction for Omani EFL students’ engagement in academic writing at the GFP level. It proposes flipping as an instructional approach which helps to address GFP students’ lack of 4 behavioural, cognitive, emotional and agentic engagement in writing courses in the Omani context. Behaviourally, students in the flipped classroom experience increased effort, improved concentration levels, persistence, communication and collaboration, and amelioration in their attitude to class attendance. It is reasonable to conclude that learners undergo cognitive growth and develop self-regulatory strategies and meta-cognitive awareness. At the level of emotional engagement, learners initially experience negative emotions such as anger and frustration, and then more positive emotions such as contentment and increased interest in the subject as they adapt to the flipped teaching-learning model. Flipping also seems to influence students’ autonomy and ability to ask questions and express opinions. It appears, however, that this approach does not influence students’ capacity to contribute to their own learning resources and activities. This study makes a valuable contribution to knowledge about students’ engagement in EFL writing courses. It revealed that a strong positive correlation exists between students’ behavioural, cognitive and emotional engagement, and that a positive correlation exists between students’ technology skills and linguistic proficiency and several aspects of their engagement. The study demonstrated, however, that no correlation exists between gender and age and students’ engagement in the flipped classroom. Furthermore, this practice-based research indicated that although flipped instruction helps to address the problem of students’ disengagement in writing courses in our context, factors such as students’ linguistic proficiency and technology skills should be taken into consideration before implementing this instructional approach in the current setting.

Although the role of school engagement in influencing children's academic competence has been recognized in past theory and research, how school engagement may mediate the relationships between ecological and personal resources and academic competence remains largely unknown. Using structural equation modeling procedures, the present study was aimed at examining the role of school engagement in mediating the associations between ecological and personal assets and academic competence. Data from 960 participants (45.6% boys) who took part in the Grades 5 and 6 assessments of the longitudinal, 4-H Study of Positive Youth Development were used. Evidence was found for a model positing two distinct school engagement components, Behavioral and Emotional, and for the role of these facets of school engagement in the relationships between developmental assets and later academic competence. Personal and ecological assets had indirect effects on later academic competence, via behavioral and emotional school engagement. Behavioral and emotional school engagement predicted academic competence differently. Emotional engagement was indirectly linked to academic competence, via behavioral engagement. Behavioral and emotional engagement also had different individual and contextual antecedents. Implications of the findings for evaluating the role of behavioral and/or emotional school engagement in academic competence and positive youth development are discussed.

Educational reforms worldwide have resulted in schools increasingly incorporating open and flexible classroom designs. Open learning spaces may contribute to a student’s behavioral and emotional school engagement directly and by facilitating classroom-based physical activity (CPA). We investigated the associations between accelerometer-assessed CPA and student ratings of task-focused behavior and attitude towards school as indicators for behavioral and emotional engagement, respectively, with the associations of gender, grade, and classroom design on CPA among 206 3rd and 5th grade students in open learning spaces and conventional classrooms. Structural equation modelling showed open classroom design to be directly associated with better attitude towards school (B = −0.336; CI95% −0.616 to −0.055), but not with task-focused behavior. The relationship between task-focused behavior and attitude towards school was statistically significant (B = 0.188; 95%CI 0.068 to 0.031). CPA was not associated with task-focused behavior and attitude towards school, while classroom design (B = 1.818; 95%CI 1.101 to 2.536), gender (B = 1.732; 95%CI 20 1.065 to 2.398), and grade (B = 1.560; 95%CI 0.893 to 2.227) were statistically significantly associated with CPA. Open learning spaces seem to be associated with better emotional engagement, which is associated with behavioral engagement. Longitudinal studies investigating associations of open learning spaces and CPA on students’ behavioral, emotional, and cognitive engagement concurrently are warranted.

The present study aimed to examine whether and to what extent university student online learning performance was influenced by individual-technology fit (ITF), task-technology fit (TTF), environment-technology fit (ETF), and whether the influence was mediated by their behavioral, emotional, and cognitive engagement. A theoretical research model was developed by integrating the extended TTF theory and student engagement framework. The validity of the model was assessed using a partial least squares structural equation modeling approach based on data collected from 810 university students. Student learning performance was influenced by TTF (β = 0.25, p < 0.001), behavioral engagement (β = 0.25, p < 0.001), and emotional engagement (β = 0.27, p < 0.001). Behavioral engagement was affected by TTF (β = 0.31, p < 0.001) and ITF (β = 0.41, p < 0.001). TTF, ITF, and ETF were observed as significant antecedents of emotional engagement (β = 0.49, p < 0.001; β = 0.19, p < 0.001; β = 0.12, p = 0.001, respectively) and cognitive engagement (β = 0.28, p < 0.001; β = 0.34, p < 0.001; β = 0.16, p < 0.001, respectively). Behavioral and emotional engagement served as mediators between fit variables and learning performance. We suggest the need for an extension to the TTF theory by introducing ITF and ETF dimensions and demonstrate the important role of these fit variables in facilitating student engagement and learning performance. Online education practitioners should carefully consider the fit between the individual, task, environment, and technology to facilitate student learning outcomes.

This study aims to examine the effects of behavioral and emotional engagement on cognitive engagement among elementary school students using structural modeling. Data were collected from 240 students in grades 4-6 using a 15-item Likert-scale questionnaire. Confirmatory Factor Analysis (CFA) was used to test construct validity and reliability, followed by Structural Equation Modeling (SEM) to examine interdimensional relationships. The results showed that behavioral engagement had a positive effect on both emotional and cognitive engagement, while emotional engagement also positively influenced cognitive engagement. However, the effects were relatively small, and emotional engagement did not significantly mediate the relationship between behavioral and cognitive engagement. These findings emphasize the role of behavioral and emotional engagement in enhancing cognitive engagement, while suggesting that other contextual factors should also be considered. The proposed model demonstrated a good fit with the data and provides a basis for understanding student engagement in primary education.

This study explores the relationship between student engagement and academic performance in Earth and Life Science among Grade 11 senior high school students. It aims to assess the levels of behavioral, emotional, and cognitive engagement and examine how demographic factors such as age, sex, and strand influence these dimensions. Using a quantitative descriptive-correlational design, data were collected through a structured engagement questionnaire and academic performance records. Results indicated a high overall level of engagement, with behavioral engagement ranking the highest and cognitive engagement the lowest. Significant differences in engagement levels were found based on demographic variables. Findings revealed a high level of student engagement (mean = 0.614), suggesting that engagement behaviors are frequently observed among non-STEM students. The correlation analysis showed no significant relationship between overall engagement and academic performance, leading to the acceptance of the null hypothesis. These results highlight the importance of identifying factors that influence student engagement. As suggested by Fredricks, Blumenfeld, and Paris (2004), enhancing behavioral, emotional, and cognitive engagement can significantly shape student learning experiences. Educators and school administrators may design targeted interventions to strengthen these engagement dimensions, fostering improved academic outcomes and enriching students' educational experiences. Keywords: Behavioral Engagement, Cognitive Engagement, Earth and Life Science, Student Performance

Interactive and adaptive scaffolds implemented in electronic mathematics textbooks bear high potential for supporting students individually in learning mathematics. In this paper, we argue that emotional and behavioral engagement may account for the effectiveness of such digital curriculum resources. Following the general model for determinants and course of motivated action, we investigated the relationship between students’ domain-specific motivational and emotional orientations (person)—while working with an electronic textbook on fractions (situation), their emotional and behavioral engagement while learning (action), and their achievement after tuition (outcome). We conducted a case-study withN= 27 students from one sixth-grade classroom, asking about the relationship between students’ motivational and emotional orientations and their emotional and behavioral engagement, and whether emotional and behavioral engagement are unique predictors of students’ cognitive learning outcomes while working with an e-textbook. For that, we designed a four-week-intervention on fractions using an e-textbook on iPads. Utilizing self-reports and process data referring to students’ interactions with the e-textbook we aimed to describe if and how students make use of the offered learning opportunities. Despite being taught in the same classroom, results indicated large variance in students’ motivational and emotional orientations before the intervention, as well as in their emotional and behavioral engagement during the intervention. We found substantial correlations between motivational and emotional orientations (i.e., anxiety, self-concept, and enjoyment) and emotional engagement (i.e., intrinsic motivation, competence and autonomy support, situational interest, and perceived demand)—with positive orientations being associated with positive emotional engagement, as expected. Although the correlations between orientations and behavioral engagement (i.e., task, exercise, and hint count, problem solving time, and feedback time) also showed the expected directions, effect sizes were smaller than for emotional engagement. Generalized linear mixed models revealed that emotional engagement predicted cognitive learning outcomes uniquely, while for behavioral engagement the interaction with prior knowledge was a significant predictor. Taken together, they accounted for a variance change of 44% in addition to prior knowledge. We conclude that when designing digital learning environments, promoting engagement—in particular in students who share less-promizing prerequisites—should be considered a key feature.

Previous research revealed the connection between students’ behavioral and emotional engagement and a supportive classroom environment. One of the primary tools teachers have to create a supportive classroom environment is effective feedback. In this study, we assessed the supportive classroom environment using the perception shared by all students from the same classroom of teachers’ use of effective feedback. We aimed to explore the effect of such an environment on students’ behavioral engagement and school identification. Using a probabilistic sample of 1,188 students from 75 classrooms across 6th, 7th, 9th, and 10th grades, we employed multilevel regression modeling with random intercept and fixed slopes. We explored the effects of both individual perceptions of teachers’ use of effective feedback and the supportive classroom environment on student engagement. The analyses identified that students who perceived that their teachers use more effective feedback had a higher level of behavioral engagement and school identification. Once we controlled the effects of these individual perceptions of teachers’ effective feedback, we still observed the effect of a supportive classroom environment on student engagement. So, in classrooms where teachers used more effective feedback creating a supportive classroom environment, students had higher school identification and behavioral engagement levels, regardless of their individual perceptions of teachers’ feedback. The association between variables remained significant even after controlling students’ characteristics (gender, nationality, mother’s level of education, history of grade retention) and classroom characteristics (grade level, type of school, number of students at grade level). Our findings support the potential of teachers’ feedback practices to foster students’ school identification and behavioral engagement to build a more inclusive school environment and value students’ diversity.