Journal articles: 'Engagement models'

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Watkins, David. "Two Models of Political Engagement." Dialogue: A Journal of Mormon Thought 42, no. 4 (2009): 100–105. http://dx.doi.org/10.5406/dialjmormthou.42.4.0100.

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Dr., Sasmita Choudhury, and Manoj Kumar Mohanty Dr. "A Conceptual Model of Employee Engagement - From the perspective of Manufacturing Industry." RESEARCH REVIEW International Journal of Multidisciplinary 03, no. 07 (2018): 290–96. https://doi.org/10.5281/zenodo.1318258.

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The concept of employee loyalty has changed in the 21st century in the backdrop of the modern workforce. Today, employers see loyalty in terms of employees’ attitude, behavior and work performance rather than the length of the service that one has rendered. Engendering loyalty from the employees is more crucial in the current knowledge economy where the human talent is the deciding factor in creating market differentiation and competitive advantage. High levels of engagement in global and domestic firms foster customer loyalty, promote retention of talent, and improve organizational performance, enhance productivity and stakeholder value. The Indian economy is currently poised as the third largest economy of the world based on Purchasing Power Parity (PPP) and the sixth on the basis of Gross Domestic Product (GDP). Currently 12% of the country’s total workforce and 50% of the total export contributed by manufacturing sector. About 100 million jobs and 25% of India’s GDP are expected from manufacturing sector by 2022. This country also diverse in the form of demographic and human capital. That’s why it is more important to understand the engagement drivers of employees closely and formulate strategies to create and retain engaged employees. This study tried to capture the all the possible drivers of engagement, required engagement environment, attributes which acts as facilitators of engagement, Signs of engagement and the derived outcomes from the perspective of Indian manufacturing sector.

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Treichler, Emily, and Yaara Zisman-Ilani. "Addressing Disparities in Treatment Engagement Models." Psychiatric Services 73, no. 8 (2022): 841. http://dx.doi.org/10.1176/appi.ps.22073008.

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Loeb, Paul Rogat. "Against Apathy: Role Models for Engagement." Academe 87, no. 4 (2001): 42. http://dx.doi.org/10.2307/40252040.

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Scherer, Emily A., Dror Ben-Zeev, Zhigang Li, and John M. Kane. "Analyzing mHealth Engagement: Joint Models for Intensively Collected User Engagement Data." JMIR mHealth and uHealth 5, no. 1 (2017): e1. http://dx.doi.org/10.2196/mhealth.6474.

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Krasny, Elke. "M2 Models and Methodologies for Community Engagement:." idea journal 14, no. 1 (2018): 120–23. http://dx.doi.org/10.37113/ideaj.vi0.73.

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   The debate over both community and planning and the large issue of their coming together in community planning reflected the economic and political changes since the 1970s. In the late twentieth century and early twenty-first century socially-driven planning more broadly addressed the issues and concerns of what community is in a locally given context and in a globally transforming world. Lived difference and situated knowledge distinguish one community from another community. The effects of globalisation, neocolonialism, neoliberalism and austerity impact communities around the globe.  

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Sawyer, Robert, Jonathan Rowe, Roger Azevedo, and James Lester. "Modeling Player Engagement with Bayesian Hierarchical Models." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 14, no. 1 (2018): 257–63. http://dx.doi.org/10.1609/aiide.v14i1.13048.

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Modeling player engagement is a key challenge in games. However, the gameplay signatures of engaged players can be highly context-sensitive, varying based on where the game is used or what population of players is using it. Traditionally, models of player engagement are investigated in a particular context, and it is unclear how effectively these models generalize to other settings and populations. In this work, we investigate a Bayesian hierarchical linear model for multi-task learning to devise a model of player engagement from a pair of datasets that were gathered in two complementary contexts: a Classroom Study with middle school students and a Laboratory Study with undergraduate students. Both groups of players used similar versions of Crystal Island, an educational interactive narrative game for science learning. Results indicate that the Bayesian hierarchical model outperforms both pooled and context-specific models in cross-validation measures of predicting player motivation from in-game behaviors, particularly for the smaller Classroom Study group. Further, we find that the posterior distributions of model parameters indicate that the coefficient for a measure of gameplay performance significantly differs between groups. Drawing upon their capacity to share information across groups, hierarchical Bayesian methods provide an effective approach for modeling player engagement with data from similar, but different, contexts.

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Broome, Kirk M., George W. Joe, and D. Dwayne Simpson. "Engagement Models for Adolescents in DATOS-A." Journal of Adolescent Research 16, no. 6 (2001): 608–23. http://dx.doi.org/10.1177/0743558401166005.

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Payne, Lisa. "Student engagement: three models for its investigation." Journal of Further and Higher Education 43, no. 5 (2017): 641–57. http://dx.doi.org/10.1080/0309877x.2017.1391186.

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Imandin, Lailah, Christo Bisschoff, and Christoff Botha. "Confirmatory analysis of the model to measure employee engagement." Problems and Perspectives in Management 14, no. 2 (2016): 93–103. http://dx.doi.org/10.21511/ppm.14(2).2016.10.

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A model to measure the employee engagement was developed by researching historical employee engagement models. These models, consisting of employee engagement constructs and their measuring criteria, have been empirically validated and factorized into seven employee engagement factors. The seven employee engagement factors (of which factor one consists of two sub-factors) were subjected to confirmatory factor analysis to ensure the inclusion of the factors in the validated model to measure employee engagement. The model was also tested for goodness of fit, and the model shows good fit indices with the Comparative Fit Index (0.799), while the good model fit of the secondary fit indices RMSEA (0.078 within a narrow margin of 0.004) and Hoelter (113 at p &amp;lt;= 0.1; 111 at p &amp;lt;= 0.05) also show satisfactory model fit. Management can use the model as diagnostic tool to measure employee engagement and to apply it in managerial decision-making. On the other hand, academics could apply the model to extend their research in employee engagement

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Byrne, Zinta, Lumina Albert, Steven Manning, and Rosemond Desir. "Relational models and engagement: an attachment theory perspective." Journal of Managerial Psychology 32, no. 1 (2017): 30–44. http://dx.doi.org/10.1108/jmp-01-2016-0006.

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Purpose Researchers have explored contextual antecedents influencing engagement at work; yet, theory and empirical evidence suggest some individuals are more or less engaged than others. Using a relational framework based on attachment theory, the purpose of this paper is to suggest that relational models influence engagement through their influence on psychological availability and psychological safety. Study 1 examined whether attachment influences variability in engagement. Study 2 examined whether these effects could be replicated, and whether attachment influences engagement via individuals’ psychological availability and safety. Design/methodology/approach Two field studies using online self-report surveys (Study 1 n=203; Study 2 n=709). Findings Attachment-avoidance and attachment-anxiety were independently associated with lower levels of engagement, and psychological conditions mediated these relationships. Research limitations/implications Relational models explain predictable variability in engagement. Employees’ ability to engage may be constrained or facilitated by their stable relational models of attachment. Originality/value The study is one of the few examining individual differences in engagement.

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D. Kaltcheva, Velitchka, Anthony Patino, Michael V. Laric, Dennis A. Pitta, and Nicholas Imparato. "Customers' relational models as determinants of customer engagement value." Journal of Product & Brand Management 23, no. 1 (2014): 55–61. http://dx.doi.org/10.1108/jpbm-07-2013-0353.

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Purpose – The authors apply Alan P. Fiske's relational models framework to customers' engagement with service firms – specifically, they propose that customers who hold different relational models for the service firm are likely to engage with the firm in dissimilar ways, thus generating different types of customer engagement value for the firm. Fiske's relational models framework is eminently suitable for studying customer-service firm engagement because it is widely adopted in the social sciences as a rigorously developed framework for conceptualizing social interactions. Design/methodology/approach – The article bridges Fiske's relational models framework and Kumar et al.'s customer engagement value framework, and conceptually demonstrates that customers employing different relational models for the service firm are likely to generate different types of customer engagement value for the firm. Findings – The article demonstrates conceptually that customers' relational models, schemata, and scripts influence how consumers engage with the firm and the type of customer engagement value accruing to the firm. Research limitations/implications – This research has implications for service firms' relationship strategies. First, service marketers can determine the desired customer engagement value(s) and then craft their customer relationship strategy so that it maximizes those engagement value(s). The article suggests relationship strategies that service firms may implement for encouraging customers to adopt different relational models. Originality/value – No research has bridged relational models theories and customer engagement value theories.

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Rahmasari, Mei Rista, and Nury Ariani Wulansari. "Employee Performance Improvement Models." Management Analysis Journal 9, no. 1 (2020): 53–61. http://dx.doi.org/10.15294/maj.v9i1.35215.

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The purpose of this research is to know the direct effect of work engagement, emotional intelligence, deep acting, and surface acting on employee performance. The population of this research is employees of 4 (four) BUMN Insurance companies in Semarang. The sampling technique used saturated sample technique and the number of samples are 121 employees. Methods of Data aollection used observation, interviews and questionnaires that were measured using a Likert scale. Methods of analysis of this study used the software of SPSS version 21. The results show that work engagement and emotional intelligence, respectively, had a significant positive effect on employee performance. Another case, with deep acting that does not show a significant effect on performance, while acting surface shows a negative effect on employee performance. The Conclusions of this study are optimal emotional intelligence will improve deep acting, surface acting, and work engagement roomates Ultimately Affects employee performance. Suggestions for companies to pay more attention to the emotional management capabilities of employees so that it does not Become a burden for employees. In addition to providing training in handling customers appropriately, and creating a comfortable working environment to support the expected emotional control in accordance with company requirements.

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Traynor, Kate. "CMS seeks pharmacists’ engagement in new care models." American Journal of Health-System Pharmacy 68, no. 23 (2011): 2206–8. http://dx.doi.org/10.2146/news110079.

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Mckoy, Temptaous, Cecilia D. Shelton, Carleigh Davis, and Erin A. Frost. "Embodying Public Feminisms: Collaborative Intersectional Models for Engagement." IEEE Transactions on Professional Communication 65, no. 1 (2022): 70–86. http://dx.doi.org/10.1109/tpc.2022.3143352.

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Williams, Ashley, Charity Evans, Deepika Nehra, Kathryn M. Stadeli, Eileen M. Bulger, and Rochelle Dicker. "Building Community: Community Engagement Models for Violence Prevention." Trauma Surgery & Acute Care Open 9, no. 1 (2024): e001483. http://dx.doi.org/10.1136/tsaco-2024-001483.

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SummaryIn 2023, the American Association for the Surgery of Trauma (AAST) hosted a panel discussion highlighting existing community engagement models for violence prevention and emphasizing the unique position of trauma surgeons to work with community stakeholders to develop these models. Four distinct programs were discussed.

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Bird, Sharon, and Melissa Latimer. "Examining models of departmental engagement for greater equity." Equality, Diversity and Inclusion: An International Journal 38, no. 2 (2019): 211–25. http://dx.doi.org/10.1108/edi-09-2017-0182.

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PurposeThe purpose of this paper is to examine two types of departmental interventions focused on creating healthier and more equitable academic departments as well as enhancing faculty members’ capacity for collective dialogue, goals and work. Both interventions were informed by the “dual-agenda” approach and focused on targeted academic units over a prolonged period.Design/methodology/approachThis paper uses a variety of qualitative and quantitative data (including National Science Foundation (NSF) ADVANCE indicator data) to assess the potential of dual-agenda informed interventions in reducing gendered structures and gendered dynamics.FindingsThe authors outline essential components of a dual-agenda model for maximizing success in creating more gender equitable work organizations and discuss why the authors are more optimistic about the dual-agenda approaches than many past researchers have been in terms of the potential of the dual-agenda model for promoting more equal opportunities in work organizations.Originality/valueMost previous dual-agenda projects referenced in the literature have been carried out in non-academic contexts. The projects examined here, however, were administered in the context of multiple academic departments at two medium-sized, public US universities. Although other NSF ADVANCE institutional transformation institutions have included extensive department-focused transformation efforts (e.g. Brown University, Purdue University and Syracuse University), the long-term benefits of these efforts are not yet fully understood; nor have systematic comparisons been made across institutions.

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Raine, John W., and Peter A. Watt. "Budgetary Models, Motivation and Engagement in Financial Collaborations." Public Management Review 15, no. 6 (2013): 878–98. http://dx.doi.org/10.1080/14719037.2012.725762.

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Boschetti, Fabio, and Matthew Andreotta. "Mental models, communication, and engagement in marine projects." ICES Journal of Marine Science 74, no. 7 (2017): 2034–39. http://dx.doi.org/10.1093/icesjms/fsw240.

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Abstract In a hypothetical decision-making situation in which a unique truth exists and each party’s aim in acquiring knowledge is to approach the truth, argumentation would be unnecessary because the best scientific theory would win the argument. Likewise, if truth is irrelevant and a perfect persuasion method is available, argumentation would also be pointless, because arguing parties, each possessing the perfect recipe, would lead a third party to switch sides endlessly. In the real world, argumentation matters because a unique truth rarely exists, information can be uncertain or vague, aims are often ambiguous if not contradictory, and acquiring knowledge can have other purposes besides approaching the truth. Marine scientists are increasingly expected to contribute to complex decision-making by providing not only scientific evidence, but also impact in the form of effective communication and persuasion. Here we review insights from different disciplines on how humans organise knowledge, beliefs, opinions, assumptions and worldviews, how these interrelate and how they affect decision-making as well as the reception of information. By focussing on the theory of mental models and the Causal Layered Analysis we also show how the structure underlying the organisation of scientific and non-scientific knowledge can be reduced to a fairly common framework. We conclude by reviewing some tools a marine scientist can employ in a stakeholder engagement process in order to better understand the audience to which scientific information needs to be delivered.

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Renjisha, R. "Parent Engagement Models That Improve Educational Outcomes in Diverse Communities." International Journal of Education and Pedagogy (IJEP) 1, no. 2 (2025): 46–53. https://doi.org/10.5281/zenodo.15341927.

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This paper examines the effectiveness of various parent engagement models in improving educational outcomes across diverse community contexts. Despite widespread acknowledgment of parental involvement's importance, significant disparities exist in engagement levels and outcomes across socioeconomic, cultural, and linguistic boundaries. Through a mixed-methods analysis of empirical research, this study identifies four key parent engagement frameworks that demonstrate measurable improvements in student achievement across diverse settings: ecological partnership models, culturally responsive engagement, digital engagement platforms, and community school initiatives. Findings suggest that successful models share common characteristics: cultural responsiveness, bidirectional communication, asset-based approaches, and systemic integration within educational institutions. The paper concludes with policy and practice recommendations for implementing contextually appropriate parent engagement strategies that address equity gaps while improving educational outcomes for all students.

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Zubek, Robert, and Ian Horswill. "Hierarchical Parallel Markov Models of Interaction." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 1, no. 1 (2021): 141–46. http://dx.doi.org/10.1609/aiide.v1i1.18731.

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Finite state techniques are popular in entertainment software production, but they complicate the modeling of certain aspects of social engagement. In this paper we examine the problem of building probabilistic finite-state interaction models that allow both hierarchical composition of behaviors, and their parallel engagement. Finally, we propose an extension that resolves the difficulties for a class of common cases.

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Tetu, Imari Cheyne, Shannon Kelly, Jun Fu, Caitlin K. Kirby, Scott Schopieray, and Stephen Thomas. "Developing Asynchronous Workshop Models for Professional Development." Communication Design Quarterly 12, no. 1 (2024): 37–43. https://doi.org/10.1145/3627691.3627695.

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Asynchronous workshops have potential as a flexible and accessible tool for instructor professional development. Translating synchronous workshops into asynchronous versions represents an opportunity to expand access to training materials, but translating across modalities is a challenge. As facilitators of the Colleges Online Learning Academy summer fellowship program, we outline our process for developing asynchronous workshops focused on pedagogy and digital learning for graduate student instructors. We evaluated participant engagement and accessibility based on survey responses (n=10) and workshop artifacts. Our four asynchronous workshops consisted of multimodal modules with video clips from the synchronous sessions and engagement opportunities on Jamboard. We found low Jamboard engagement from asynchronous participants, but high engagement in multimodal modules. Potential barriers to access included mental health, Wi-Fi access, English language comprehension, and a lack of discussion, but many participants (4 of 9) reported no access barriers. We provide recommendations for developing engaging, accessible, and content-rich asynchronous workshops from synchronous workshop materials.

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Tetu, Imari Cheyne, Shannon Kelly, Jun Fu, Caitlin K. Kirby, Scott Schopieray, and Stephen Thomas. "Developing Asynchronous Workshop Models for Professional Development." Communication Design Quarterly 12, no. 3 (2024): 37–43. https://doi.org/10.1145/3563890.3713036.

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Asynchronous workshops have potential as a flexible and accessible tool for instructor professional development. Translating synchronous workshops into asynchronous versions represents an opportunity to expand access to training materials, but translating across modalities is a challenge. As facilitators of the Colleges Online Learning Academy summer fellowship program, we outline our process for developing asynchronous workshops focused on pedagogy and digital learning for graduate student instructors. We evaluated participant engagement and accessibility based on survey responses (n=10) and workshop artifacts. Our four asynchronous workshops consisted of multimodal modules with video clips from the synchronous sessions and engagement opportunities on Jamboard. We found low Jamboard engagement from asynchronous participants, but high engagement in multimodal modules. Potential barriers to access included mental health, Wi-Fi access, English language comprehension, and a lack of discussion, but many participants (4 of 9) reported no access barriers. We provide recommendations for developing engaging, accessible, and content-rich asynchronous workshops from synchronous workshop materials.

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Mansouri, M., M. Holgerson, M. M. Khonsari, and W. Aung. "Thermal and Dynamic Characterization of Wet Clutch Engagement With Provision for Drive Torque." Journal of Tribology 123, no. 2 (2000): 313–23. http://dx.doi.org/10.1115/1.1329856.

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Wet clutches that handle the gearshifts in automatic transmission undergo severe thermal stresses due to the occurrence of large temperature gradients during engagement. To accurately design wet clutches, better models to simulate the engagement process are needed. This work presents a finite element model for simulating wet clutch engagements. The total friction coefficient was used to describe the different lubrication regimes that a wet clutch engagement undergoes. The model also includes provision for drive torque that realistically simulates the engine torque of a car. The results of the simulations are successfully verified by comparison with laboratory experiments on a testrig specially designed to accommodate the drive torque, covering a wide range of typical engagements. Excellent agreement between experiment and simulations is reported in terms of both the dynamics of the engagement and the thermal characteristics. The results are indicative of the utility of the model as a useful engineering tool.

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Haetami, Aceng, Abena Boateng, and Ricardo Martinez. "Flipped Classroom Models: Revolutionizing Learning in Higher Education." International Journal of Educational Narratives 3, no. 1 (2025): 1–11. https://doi.org/10.70177/ijen.v3i1.1690.

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Bacground. The traditional lecture-based model of teaching in higher education has faced increasing criticism due to its limited engagement and ability to foster active learning. In response, the flipped classroom model has emerged as a promising alternative, where students engage with instructional content outside the classroom and use class time for collaborative and interactive activities. This pedagogical shift aims to enhance student learning outcomes, promote critical thinking, and increase overall engagement. Purpose. This study aims to investigate the effectiveness of flipped classroom models in higher education, focusing on their impact on student engagement, academic performance, and learning outcomes. Method: A mixed-methods approach was employed, combining quantitative analysis of student performance data with qualitative insights from surveys and interviews. A sample of 200 students from five different universities participated in flipped classroom courses, and their learning outcomes were compared to those of students in traditional lecture-based courses. Data were collected at the beginning and end of the semester to assess changes in engagement and academic performance. Results: The study found that students in flipped classrooms showed significantly higher levels of engagement and academic performance compared to their peers in traditional settings. Students reported increased satisfaction with the learning process, particularly in terms of collaborative learning and self-paced study. Conclusion: The flipped classroom model proves to be an effective strategy for enhancing student engagement and improving learning outcomes in higher education. This approach fosters a more active, student-centered learning environment that better prepares students for real-world challenges.

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Stefansson, Kristjan K., Steinunn Gestsdottir, G. John Geldhof, Sigurgrimur Skulason, and Richard M. Lerner. "A Bifactor Model of School Engagement." International Journal of Behavioral Development 40, no. 5 (2016): 471–80. http://dx.doi.org/10.1177/0165025415604056.

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School engagement involves cognitive, emotional, and behavioral components that overlap conceptually. This conceptual ambiguity has led to measures that have either consisted of one general factor or separate correlated factors. However, neither approach can sufficiently account for both the uniqueness and the overlap of the subcomponents. The bifactor model has been recommended to determine the degree to which a measure is unidimensional versus multidimensional. In this study, we examined the validity of a multidimensional measure of school engagement in adolescence, the Behavioral-Emotional-Cognitive School Engagement Scale (BEC-SES; Li & Lerner, 2013), by comparing the model fit and predictive power of the widely-used one- and three-factor models with a bifactor model. Using data from 561 youth in Iceland (46% girls, Mage at Wave 1 = 14.3 years, SD = 0.3), only the multidimensional models (i.e., the three-factor and bifactor models) gave a good fit to the data. We then assessed the predictive power of the multidimensional models for academic achievement. The addition of academic achievement as an outcome variable to the bifactor model revealed that general school engagement, as well as specific behavioral engagement, predicted achievement. These findings are distinct from previous results using three-factor models, which indicated that behavioral engagement alone predicted later achievement. The results of the current study support the use of a bifactor model when using measures of school engagement.

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Mahmood, Nasir, Sohail Masood Bhatti, Hussain Dawood, Manas Ranjan Pradhan, and Haseeb Ahmad. "Measuring Student Engagement through Behavioral and Emotional Features Using Deep-Learning Models." Algorithms 17, no. 10 (2024): 458. http://dx.doi.org/10.3390/a17100458.

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Students’ behavioral and emotional engagement in the classroom environment may reflect the students’ learning experience and subsequent educational outcomes. The existing research has overlooked the measurement of behavioral and emotional engagement in an offline classroom environment with more students, and it has not measured the student engagement level in an objective sense. This work aims to address the limitations of the existing research and presents an effective approach to measure students’ behavioral and emotional engagement and the student engagement level in an offline classroom environment during a lecture. More precisely, video data of 100 students during lectures in different offline classes were recorded and pre-processed to extract frames with individual students. For classification, convolutional-neural-network- and transfer-learning-based models including ResNet50, VGG16, and Inception V3 were trained, validated, and tested. First, behavioral engagement was computed using salient features, for which the self-trained CNN classifier outperformed with a 97%, 91%, and 83% training, validation, and testing accuracy, respectively. Subsequently, the emotional engagement of the behaviorally engaged students was computed, for which the ResNet50 model surpassed the others with a 95%, 90%, and 82% training, validation, and testing accuracy, respectively. Finally, a novel student engagement level metric is proposed that incorporates behavioral and emotional engagement. The proposed approach may provide support for improving students’ learning in an offline classroom environment and devising effective pedagogical policies.

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Jeong Hee Hong, Kyung Min Seo, Moon Gi Seok, and Tag Gon Kim. "Interoperation between Engagement-and Engineering-level Models for Effectiveness Analyses." Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 8, no. 3 (2011): 143–55. http://dx.doi.org/10.1177/1548512910389483.

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System effectiveness analyses are a longstanding challenge in defense modeling and simulation. While some techniques are accomplished through using an engagement-level model alone with given parameterized weapon performance data, this approach is prone to errors because of insufficient behavior information from the weapon systems. In order to overcome these limitations, engagement-level models should be supported by engineering-level models representing the detailed behavior of weapons. Hence, this paper proposes an interoperation approach between the engagement and engineering-level models. Our approach produces meaningful results in terms of various engagement tactic alternatives for the suitable performance of weapons under given situations, such as operational environments, operational errors, and so on. The proposed method is demonstrated through an anti-torpedo combat simulation, including the engagement and the engineering-level models. We perform experiments by varying tactical military scenarios or performance indices of decoy systems. Experimental results show suggestions for operational tactics and weapons specifications in order to meet requirements.

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Shashikant, Nishant Sharma. "Review of Most Used Urban Growth Models." International Journal of Advanced Research in Engineering and Technology (IJARET) 10, no. 3 (2019): 397–405. https://doi.org/10.5281/zenodo.8169002.

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Smart urban growth management is a planning and management approach that seeks to promote sustainable development and quality of life in urban areas. It involves a range of strategies and practices that aim to balance economic growth, social equity, and environmental sustainability, while ensuring that urban areas remain livable and resilient over the long term. Planning and zoning: Effective land use planning and zoning can help guide growth and development in ways that support community goals and values, such as preserving open space, promoting affordable housing, and encouraging mixed-use development. Transportation planning: Smart urban growth management also involves transportation planning that prioritizes walking, cycling, and public transit, and reduces dependence on single-occupancy vehicles. This can reduce traffic congestion, improve air quality, and enhance community connectivity. Environmental protection: Smart urban growth management seeks to protect and enhance natural resources, such as waterways, wetlands, and green spaces, and reduce the environmental impact of development. Community engagement: Effective community engagement is essential for ensuring that urban growth management strategies reflect the needs and priorities of residents, businesses, and other stakeholders.

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Mvana, Siyamthanda Wendy. "Exploring engagement theories and models to enhance teacher retention strategies." Multidisciplinary Reviews 8, no. 1 (2024): 2025007. http://dx.doi.org/10.31893/multirev.2025007.

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This study thoroughly examines the two complex theories related to work engagement in the context of teacher retention. Emphasising the crucial significance of achieving a harmonious and cohesive degree of engagement, it aims to address the urgent problem of teacher attrition. The study creates a unified narrative that redefines teacher retention, especially in marginalised communities. It reframes the topic by integrating Kahn's theory of engagement with Schaufeli et al. model of work engagement. These two theoretical frameworks provide teachers with a deeper comprehension and direction in navigating the complexities of their profession, assisting them in achieving long-term commitment. This study offers both theoretical insight and practical recommendations for educational institutions and policymakers to enhance teacher retention.

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Joseph, Genimon Vadakkemulanjanal, Kennedy Andrew Thomas, and Alex Nero. "Impact of Technology Readiness and Techno Stress on Teacher Engagement in Higher Secondary Schools." Digital Education Review, no. 40 (December 27, 2021): 51–65. http://dx.doi.org/10.1344/der.2021.40.51-65.

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Rapid technology advancements resulted a fundamental shift in the education sector which redefined the teaching-learning process and teacher engagement. Based on numerous studies on work engagement models and technology readiness, this study explores, how the teachers’ readiness to embrace educational technologies, impact on teacher engagement. With stratified cluster sampling model, data were collected from principals, managers, students and 122 faulty were participated in this quantitative study using standardized tools. Teachers were highly engaged with students-colleagues and varied across experience/age groups. Technology readiness factors positively impacted on social engagements with students-colleagues. As education technology usage is exponential, more future research is needed.

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Czarnecka, Marzena, Grzegorz Kinelski, Magdalena Stefańska, Mateusz Grzesiak, and Borys Budka. "Social Media Engagement in Shaping Green Energy Business Models." Energies 15, no. 5 (2022): 1727. http://dx.doi.org/10.3390/en15051727.

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Recent years have seen an increase in the role of social media in the communication of energy sector companies (ESCs) with consumers. Currently, consumers look for information, create it themselves, and share it with other Internet users. eWOM communication means that energy companies, firstly, must be present in social media so that consumers can get to know them better, and secondly, they must consciously shape their image according to the expectations of their customers. One-way communication, such as customer satisfaction measurements, is no longer enough to know their preferences. Market trends indicate that for current buyers—both consumer and non-consumer products—the image of a “green product” or a “green company” is expected. Only a few companies report that they are harmful for environment. All companies report that they are generally community friendly. The consumer would like to know, in particular, about the harmfulness to the environment. Thus, there is a knowledge gap that the companies are not filling. In addition to the advertised satisfaction indicators, you can also test customers’ perceptions of environmental responsibility. That is, the research and results in the area of social responsibility must also be accompanied by environmental responsibility. Therefore, the article aims to indicate whether the level of consumer engagement in social media affects the perception of the green energy business model and how the attitude and pro-environmental behavior of social media users affects this perception. The paper also identifies factors related to social media that influence the perception of ESCs.

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Jerónimo, Carlos, Leandro Pereira, N. A. Jo�ã, and o. Lourenço. "Strategic supplier management: from contractual models to engagement partnerships." International Journal of Process Management and Benchmarking 12, no. 1 (2022): 13. http://dx.doi.org/10.1504/ijpmb.2022.120408.

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Lawrence, Jill. "Two Models for Facilitating Cross-cultural Communication and Engagement." International Journal of Diversity in Organizations, Communities, and Nations: Annual Review 6, no. 6 (2007): 73–82. http://dx.doi.org/10.18848/1447-9532/cgp/v06i06/39288.

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Kath, James E., and Aleksandra Baranczak. "Target engagement approaches for pharmacological evaluation in animal models." Chemical Communications 55, no. 63 (2019): 9241–50. http://dx.doi.org/10.1039/c9cc02824b.

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Lourenço, Jo�ão, Carlos Jeronimo, and Leandro Pereira. "Strategic Supplier Management: from contractual models to engagement partnerships." International Journal of Process Management and Benchmarking 1, no. 1 (2020): 1. http://dx.doi.org/10.1504/ijpmb.2020.10030897.

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Beattie, S., and M. Davies. "A test of engagement versus disengagement in catastrophe models." British Journal of Psychology 101, no. 2 (2010): 361–71. http://dx.doi.org/10.1348/000712609x467891.

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Billow, Richard M. "Models of Therapeutic Engagement Part II: Sincerity and Authenticity." International Journal of Group Psychotherapy 60, no. 1 (2010): 29–58. http://dx.doi.org/10.1521/ijgp.2010.60.1.29.

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Li, Feng, Guangfan Zhang, Wei Wang, et al. "Deep Models for Engagement Assessment With Scarce Label Information." IEEE Transactions on Human-Machine Systems 47, no. 4 (2017): 598–605. http://dx.doi.org/10.1109/thms.2016.2608933.

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Rassiwala, Jasmine, Muthiah Vaduganathan, Mania Kupershtok, Frank M. Castillo, and Jessica Evert. "Global Health Educational Engagement—A Tale of Two Models." Academic Medicine 88, no. 11 (2013): 1651–57. http://dx.doi.org/10.1097/acm.0b013e3182a6d0b0.

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Yan, Lijuan, Xiaotao Wu, and Yi Wang. "Student engagement assessment using multimodal deep learning." PLOS One 20, no. 6 (2025): e0325377. https://doi.org/10.1371/journal.pone.0325377.

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Student engagement assessment plays an important role in enhancing students’ positive performance and optimizing teaching methods. In this paper, a multimodal deep learning framework is proposed for student engagement assessment. Based on this framework, we propose a method for engagement assessment that utilizes data from three modalities: video, text, and logs. This method implements the extraction of engagement indicators, the fusion of asynchronous data, the use of deep learning models to evaluate engagement levels, and the use of gradient magnitude mapping to further distinguish subtle differences between engagement levels. In subsequent empirical studies, we explore the applicability of several popular deep CNN models in this method and validate the reliability of the engagement quantification results using statistical methods. The analysis results demonstrate that the framework, which combines multimodal asynchronous data fusion and deep learning models to assess engagement, is both effective and practical.

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Collier, Ben, and Matt Woodburn. "Rethinking Collection Management Data Models." Biodiversity Information Science and Standards 6 (August 23, 2022): e91297. https://doi.org/10.3897/biss.6.91297.

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The data modelling of physical natural history objects has never been trivial, and the need for greater interoperability and adherence to multiple standards and internal requirements has made the task more challenging than ever. The Natural History Museum's internal RECODE (Rethinking Collections Data Ecosystems; see Dupont et al. 2022) programme has taken the approach of creating a data model to fit these internal and external requirements, rather than try and force an existing data model to work with our next generation collections management system (CMS) requirements. In this regard, community standards become vitally important, and existing and emerging standards and models like Spectrum, Darwin Core, Access to Biological Collection Data (ABCD) (Extended for Geosciences (EFG)), Latimer Core and The Conceptual Reference Model from the International Committee for Documentation (CIDOC CRM) have and will be used heavily to inform this work. The poster will provide a starting point for: publicly sharing and discussing the work that the RECODE programme has done; eliciting ideas that members of the community may have regarding its continuing improvement.We have concentrated on creating a backbone for the data model, from collecting, through the object curation to the scientific identification. This has yielded two significant outcomes:The Collection Object: Traditional CMS data models treat each specimen as a single record in the database. The RECODE model recognises that there are a number of different concepts that need their own entities:Collected material: the specimens collected in the field are not always fully identified or separated into discrete items.Stored object: the aim of the RECODE model is to treat all objects as the same type of entity, with relationships between them enhancing the data. For example, a collection object is defined as a discrete object that can be moved and loaned independently. Its specific type (e.g., specimen, preparation, derivation) is given by its relationships to other collection objects.Identifiable item: what can be taxonomically identified does not necessarily have a 1-to-1 relationship with the stored objects. One item may contain multiple species (e.g., a parasite and host; a rock containing many minerals) or one species may be split across many objects (e.g., long branches on two or more herbarium sheets; large skeletons stored in separate locations).The Collection Level Description (CLD): This is a construct to enable the attachment of descriptive and quantitative data to groups of collection objects, rather than individual collection object. There will always be a need for an inventory which represents the basic holdings, organisation and indexing of collections as well as a variety of use cases for grouping collection objects and attaching information at the group level.The next challenge is to integrate the concepts more closely with each other to provide the best possible description of the collection and make it as shareable as possible. Some of the current challenges being addressed are:An object group may represent a heterogenous group of objects.There will be multiple parallel CLD schemes for different purposes.Different attributes and metrics will be relevant to different schemes.For some use cases, we need to be able to quantify relationships between an object group and its attributes as well as attaching metrics to the object group itself.We also need to be able to reflect relationships between object groups.These challenges necessitate a data model that has a considerable degree of flexibility but enables rules and constraints to be introduced as appropriate for the different use cases. It is also important that, wherever possible, the model uses the same attributes as individual collection objects, to allow object groups to be implicitly linked to collection object records through common attributes as well as explicitly linked within the model. The aim of the conceptual model is to reflect these requirements.

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Kao, Dominic, and D. Fox Harrell. "Exploring the Use of Role Model Avatars in Educational Games." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 11, no. 3 (2021): 29–35. http://dx.doi.org/10.1609/aiide.v11i3.12814.

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Research has indicated that role models have the potential to boost academic performance. In this paper, we describe an experiment exploring role models as game avatars in an educational game. Of particular interest are the effects of these avatars on players' performance and engagement. Participants were randomly assigned to a condition: a) user selected role model avatar, or b) user selected shape avatar. Results suggest that role models are heavily preferred. African American participants had higher game affect in the role model condition. South Asian participants had higher self-reported engagement in the role model condition. Participants that completed <= 1 levels had higher performance in the role model condition. General trends suggest that the role model's gender and racial closeness with the player, could play a role in player performance and self-reported engagement as consistent with the social science literature.

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Eny Purwandari and Khoirunnisa. "Student Engagement Models: Parental Support, Academic Self-Efficacy, and the Teacher-Student Relationship." Jurnal Iqra' : Kajian Ilmu Pendidikan 8, no. 2 (2023): 481–94. http://dx.doi.org/10.25217/ji.v8i2.4010.

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Student engagement is the basis for academic and social success in online learning. The study aimed to examine the measurement and structural models and empirically test the relationship between parental support, academic self-efficacy, teacher-student relationship, and student engagement. The number of research samples was 323 junior high school students in Cirebon City, coming from 4 schools (public and private) which were obtained by multistage cluster random. The instrument uses a scale of student engagement, parental support, academic self-efficacy, and teacher-student relationship. Data analysis using structural equation modeling (SEM) with LISREL 8.8 program. The results showed that the overall fit test of the student engagement model was fit: Chi-square (p) = 146.71 (.00), df = 59, RMSEA = .068, SRMR =.05; CFI = .99, NNFI =.99; GFI = .93. The student engagement model is supported by parental support, academic self-efficacy, and the teacher-student relationship. The findings have contributed to strategies for increasing student engagement through parental support, teacher-student relationships, and academic self-efficacy. Keywords: Student Engagement Model, Parental Support, Academic Self-Efficacy

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T, Aravinthan. "Employee Engagement and Its Impact on Organizational Performance." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem42684.

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Employee engagement is a pivotal element in ascertaining corporate performance. This study examines the concept of employee engagement, its primary determinants, and its effect on organizational performance. The research analyze several engagement models and their impact on productivity, staff retention, and overall workplace satisfaction. An examination of current literature and case studies reveals a correlation between elevated engagement levels and enhanced business outcomes. The results indicate that firms that invest in employee engagement techniques achieve more profitability, innovation, and customer happiness. Key words: Employee engagement, Corporate performance, Organizational performance, Engagement models, Productivity, Innovation, Customer happiness, Determinants of engagement, Employee satisfaction

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Shyamakrishna Siddharth Chamarthy, Murali Mohana Krishna Dandu, Raja Kumar Kolli, Dr Satendra Pal Singh, Prof.(Dr) Punit Goel, and Om Goel. "Machine Learning Models for Predictive Fan Engagement in Sports Events." International Journal for Research Publication and Seminar 11, no. 4 (2020): 280–301. http://dx.doi.org/10.36676/jrps.v11.i4.1582.

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In the realm of sports, fan engagement has become a pivotal element for enhancing the overall experience and maximizing revenue opportunities. This paper explores the application of machine learning models to predict fan engagement during sports events, offering insights that can inform marketing strategies, game-day operations, and fan interaction initiatives. Utilizing historical data on fan behavior, attendance, social media interactions, and game statistics, various machine learning algorithms—such as regression analysis, decision trees, and neural networks—are employed to develop predictive models. These models are designed to identify patterns in fan engagement and forecast future behaviors, allowing teams and event organizers to tailor their marketing efforts and improve fan experiences. Additionally, the study highlights the importance of real-time data analysis, enabling stakeholders to make informed decisions during events. By integrating these predictive models with live data feeds, sports organizations can dynamically adjust their engagement strategies, ensuring they resonate with fans' preferences and expectations. The findings underscore the potential of machine learning to revolutionize fan engagement, transforming passive spectators into active participants. Ultimately, this research contributes to a deeper understanding of how technology can enhance the sports experience, fostering loyalty and increasing overall satisfaction among fans. The implications of these models extend beyond individual teams, providing a framework that can be adapted across various sports disciplines, ultimately enriching the landscape of sports marketing and fan interaction.

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Pinto, Rogério M., Sunggeun (Ethan) Park, Rashun Miles, and Pei Ni Ong. "Community engagement in dissemination and implementation models: A narrative review." Implementation Research and Practice 2 (January 2021): 263348952098530. http://dx.doi.org/10.1177/2633489520985305.

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Background: Responding to the growing demand for scientific understanding of adoption and uptake of evidence-based interventions (EBIs), numerous dissemination and implementation (“D&I”) models have been proposed in the extant literature. This review aimed to identify community-specific constructs with the potential to help researchers engage community partners in D&I studies or deploy EBIs. Methods: We identified 74 D&I models targeting community-level changes. We built on Tabak et al.’s narrative review that identified 51 D&I models published up to 2012 and identified 23 D&I models published between 2012 and 2020 from the Health Research & Practice website (16 models) and PubMed database (7 models). Three coders independently examined all 74 models looking for community-specific engagement constructs. Results: We identified five community engagement constructs: (1) Communication, (2) Partnership Exchange, (3) Community Capacity Building, (4) Leadership, and (5) Collaboration. Of the 74 models, 20% reflected all five constructs; 32%, four; 22%, three; 20%, two; and 5%, only one. Few models with strong community content have been introduced since 2009. Conclusion: This article bridges the community-engaged and D&I research literature by identifying community engagement constructs reflected in existing D&I models, targeting community-level changes. Implications for future research and practice are discussed. Plain language summary Responding to the growing demand for scientific understanding of adoption and uptake of evidence-based interventions (EBIs), numerous dissemination and implementation (“D&I”) models have been proposed. This review aimed to identify community-specific constructs with the potential to help researchers engage community partners in D&I studies or deploy EBIs. We identified 74 D&I models targeting community-level changes, published between 2012 and 2020. Three coders independently examined all 74 models looking for community-specific engagement constructs. We identified five community engagement constructs: (1) Communication, (2) Partnership Exchange, (3) Community Capacity Building, (4) Leadership, and (5) Collaboration. Of the 74 models, 20% reflected all five constructs; 32%, four; 22%, three; 20%, two; and 5%, only one. This article identified community engagement constructs reflected in existing D&I models targeting community-level changes. Implications for future research and practice are discussed.

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Salvioni, Daniela, and Alex Almici. "Circular Economy and Stakeholder Engagement Strategy." Symphonya. Emerging Issues in Management, no. 1 (2020): 26. http://dx.doi.org/10.4468/2020.1.03salvioni.almici.

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The transition from the linear economy to the circular one is an epochal challenge for firms. It requires rethinking of the ways to create value according to circular business models. In this context, adoption of a stakeholder engagement strategy based on principles such as involvement, dialogue, and effective fulfillment of stakeholders’ expectations is becoming increasingly relevant. This study analyzes the role of stakeholder engagement with respect to the success of circular business models by identifying the main factors that deserve attention in order to ensure an effective shift toward the circular economy.

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Qiu, Yuxiang, Karim Djemili, Denis Elezi, et al. "A Toolbox for Modelling Engagement with Educational Videos." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 21 (2024): 23128–36. http://dx.doi.org/10.1609/aaai.v38i21.30358.

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With the advancement and utility of Artificial Intelligence (AI), personalising education to a global population could be a cornerstone of new educational systems in the future. This work presents the PEEKC dataset and the TrueLearn Python library, which contains a dataset and a series of online learner state models that are essential to facilitate research on learner engagement modelling. TrueLearn family of models was designed following the "open learner" concept, using humanly-intuitive user representations. This family of scalable, online models also help end-users visualise the learner models, which may in the future facilitate user interaction with their models/recommenders. The extensive documentation and coding examples make the library highly accessible to both machine learning developers and educational data mining and learning analytics practitioners. The experiments show the utility of both the dataset and the library with predictive performance significantly exceeding comparative baseline models. The dataset contains a large amount of AI-related educational videos, which are of interest for building and validating AI-specific educational recommenders.

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Leidig, Paul, and William Oakes. "Model for Project-Based Community Engagement." International Journal for Service Learning in Engineering, Humanitarian Engineering and Social Entrepreneurship 16, no. 2 (2021): 1–13. http://dx.doi.org/10.24908/ijsle.v16i2.14809.

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Community engagement experiences in STEM fields are typically project-based, which introduces components and considerations not explicitly addressed by models commonly used in community-engaged learning more broadly. This paper is a narrative on how we reflected on current models, developed a new one designed for project-based community engagement experiences, and where we see it being useful into the future. While existing models can be useful for STEM-based project teams, project-based engagement raises further questions and presents additional features, such as the existence of the dual value generators of both the project deliverable and project process. We concentrated on providing a macroscopic view of project-based community engagement to organize aspects of a program and maximize positive features while managing resources. The visual model has been developed to facilitate reflection on program design, development, operation, and assessment. It can facilitate intentional consideration, definition, and organization of stakeholders, project deliverables, project process, resources input, and value produced. We foresee several potential uses for this model as a conceptual framework and practical tool for community engagement experiences and programs.

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Journal articles on the topic 'Engagement models'

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