Recent News and Announcement

Lab welcomes two new members

Two new members have joined our lab this Fall—Jessica Bates and Mike Frazier—who are first year PhD students in the Learning Technologies program.

Jessica has been an educator and online course developer since 2008. She currently is the K-8 Curriculum Supervisor for Virtual Virginia, a program of the Virginia Department of Education. In this role, she oversees course design and development for multiple levels and content areas. She also provides training in instructional design for online course developers. Her academic interests include instructional design and development, technology integration in teaching and learning, social emotional learning in the virtual setting, and learner’s motivation and engagement in the digital environment.

Mike joins us after teaching English, Writing, and Education Technology for eleven years in K-12 and Higher Education settings in both central Ohio and South Korea. With degrees and certifications in English, English Education, Education Technology, and Teacher Leadership, he is now interested in furthering the field through research and professional development, keeping one foot in the classroom and one foot in academia.

Publication on Teachers’ Knowledge and Beliefs in Technology Integration

Lu, G., Liu, Q., Xie, K., Long, T., Zheng, X. (online first). Quality or quantity: How do teachers’ knowledges and beliefs ‘persuade’ their technology integration in a massive government-led training programme? The Asian-Pacific Education Researcher. DOI: https://doi.org/10.1007/s40299-022-00668-z (SSCI Journal; Impact Factor: 2.561)

Abstract
Technology integration refers to the process of innovation diffusion, from understanding technology knowledge to achieving a high level quality of technology usage. To address the gap in research regarding the critical factors that influence K-12 teachers’ practice of technology integration at the initial stage of a massive government-led training programme in rural areas, this study sought to explore the comprehensive effects of teachers’ technological pedagogical content knowledge (TPACK) and beliefs on their technology integration. Participants included 267 in-service K-12 teachers from four pilot schools in a remote rural area in north-western China. We found that: (a) T-related knowledge positively predicted the teachers’ technology integration quality and quantity, while T-unrelated knowledge negatively influenced technology integration quality and quantity; (b) the positive valence of teachers’ beliefs (PVTBs) was positively related to technology integration quality, the negative valence of teachers’ beliefs was negatively related to technology integration quantity; (c) the PVTBs impacted the quality and quantity of technology integration through T-related knowledge; and (d) gender significantly moderated the impact of positive beliefs and T-related knowledge on technology integration. This study suggests that improving K-12 teachers’ technology integration in rural areas requires prioritizing professional development programmes that improve teachers’ beliefs in the initial stage of technology diffusion.

Publication on Multilevel Latent State-Trait Models

Vongkulluksn, V.W. & Xie, K. (2022). Multilevel latent state-trait models with experiential sampling data: An illustrative case of examining situational engagement. Open Education Studies, 4(1), 252-272. https://doi.org/10.1515/edu-2022-0016 (Open Access with Free Downloads)

Abstract
Learning processes often occur at a situational level. Changes in learning context have implications on how students are motivated or are able to cognitively process information. To study such situational phenomena, Experience Sampling Method (ESM) can help assess psychological variables in the moment and in context. However, data collected via ESM is voluminous and imbalanced. Special types of statistical modeling are needed to handle this unique data structure in order to maximize its potential for scientific discovery. The purpose of this paper is to illustrate how Latent State-Trait modeling used within a multilevel framework can help model complex data as derived by ESM. A study of situational engagement is presented as an illustrative case. We describe methodological considerations which facilitated the following analyses: (1) Decomposition of trait-level and state-level engagement; (2) Group differences in variance decomposition, and (3) Predicting state component of engagement. Discussions include the relative advantages and disadvantages of ESM and multilevel Latent State-Trait modeling in facilitating situational psychological research.

Keywords:Experiential Sampling; Situational Engagement; Latent Variable Modeling; Latent State-Trait Modeling

Publication on Motivation for Online Language Learning

Jiang, Z. & Xie, K. (2022). Motivating online language learners: From theory to design strategies. Journal of Technology and Chinese Language Teaching, 13(1), 1-25. (Open Access with Free Downloads)

Abstract
The development of online education has posed new opportunities to language learning, especially for learning a second language such as Chinese. However, challenges also exist. One of the major concerns is motivating students to learn in an isolated and independent learning environment. Research in online education has revealed that successful online learning depends mostly on learners’ motivation and their ability to manage the learning process. However, motivation in online Chinese learning settings is an understudied area in the extant literature. This paper introduces the self-determination theory (SDT) as an appropriate theoretical framework for addressing learning and motivation challenges in online Chinese learning. This paper also explores the design of online Chinese learning environments from the perspective of SDT. It begins with a brief overview of the motivation issues in online Chinese learning and follows with the discussion of the application of the SDT theoretical framework in an online Chinese learning context. In addition, it reviews the findings in the literature of online Chinese learning and proposes instructional design strategies that can promote and support student motivation.

在线教育的发展为中文语言学习带来的新的机遇和挑战。如何激发并保持学生学习动机是在线学习中的一个重要问题之一。在线教育研究表明,学生的学习动机和管理学习过程的能力是影响在线学习的重要因素。然而,目前关于在线中文学习动机的研究尚少。 本文以自我决定学习理论为指导框架,讨论如何从学习环境设计的角度来支持中文在线学习动机的发展。本文先概述了中文在线学习中的学习动机问题,然后介绍了自我决定理论在中文学习环境中的应用,并基于目前文献研究提出相关的教学设计策略以支持学生学习动机的发展。

Mitchell Shortt successfully defended his dissertation


Congratulations to Mitchell Shortt — a doctoral student in the Learning Technologies PHD program. He successfully defend his doctoral dissertation entitled “Online Racial Discrimination, the Academic Outcomes, and How Students Defend Themselves“! In his dissertation, Mitch examined the prevalence of online racial discrimination (ORD) among adolescents and young adults, how ORD impacted their academic outcomes, and how they defended themselves from ORD. Thanks to Mitchell’s committee: Kui Xie (advisor), Karen Beard, Tzu-Jung Lin, and Carolyn M. Sommerich (external examiner). Please join us to congratulate Dr. Mitchell Shortt!!! (more…)

Presentations at AECT 2022

In the upcoming 2022 Annual Meeting for Association for Educational Communications and Technology (AECT) in October 24-28, 2022, Las Vegas, NV, our lab members will be involved in the following presentations:

Shortt, M., Beard, K., & Xie, K. (2022, October). Online Racial Discrimination, the Academic Outcomes, and How Students Defend Themselves. Paper to be presented at the convention of the Association for Educational Communications and Technology, Las Vegas, NV.

Abstract: This research explored the effects of online racial discrimination (ORD) on adolescent and young adult students’ academic outcomes and social-emotional well-being with a focus on Black, Asian, and White racial groups. A mixed methods explanatory sequential approach was utilized. Results showed that several outcomes were significantly influenced from experiencing ORD, including students’ academic persistence. Findings reveal the prevalence of ORD, and can inform interventions, as well as counselors, administrators, teachers, and parents. (more…)

Publication on Seat Location and Social Interaction in Smart Classroom

Wang, J., Xie, K., Liu, Q., Long, T., & Lu, G. (2022). Examining the effect of seat location on students’ real-time social interactions in a smart classroom using experience sampling method. Journal of Computers in Education, https://doi.org/10.1007/s40692-022-00229-9.

Abstract
While prior research has examined the impact of seats on students’ performance in the classroom, no agreement has reached on how seat locations influence students’ social interactions, especially in technology-enhanced classrooms. This study seeks to understand how different seats of smart classrooms are associated with student real-time social interactions. In this study, we examine how the situational and individual factors as the key variables may account for the students’ real-time social interactions. Specifically, data on real-time social interactions and different seats were collected using the experience sampling method (ESM) from 36 sophomores at a university in central China, resulting in 180 ESM responses. The results of Multilevel Analysis showed that the students’ seat location and the week number within the individual had a significant impact on the student’s real-time social interactions, while the gender and mastery goal of students affected their social interactions among individuals. Meanwhile, the seat fluctuations of students who participated in the smart classroom presented three typical types: front row stable type, rear stable row type, and fluctuating type.

Students Deserve an Answer When They Ask, “When Will I Ever Use This?” In Math Class

By Margaret A. Bowman, Ph.D., Academic Designer at McGraw Hill

Here’s How Technology Can Help
Every math teacher has likely heard it before: “When am I ever going to use this?”

While some students quickly pick up anything mathematical, others mumble through class about how they don’t like math, they aren’t good at math, math just isn’t “their thing”, and they’re never going to use it in real life. Students who think this way often have had a bad experience with math and struggle to connect what they learn in school to their own lives, both current and future. Research shows, though, that motivation is critical to short- and long-term mathematical performance (Eccles & Wigfield, 2002). Without intervention, these students’ motivation for learning math is only going to get worse. (more…)

Meta-Analysis on Community of Inquiry in Online Learning

Martin, F., Wu, T., Wan, L. & Xie, K. (2022). Meta-analysis of research on community of inquiry and its impact of student learning outcomes. Online Learning,26(1), 325-359. DOI: 10.24059/olj.v26i1.2604

Abstract
The Community of Inquiry (CoI) framework describes three essential presences (i.e., teaching presence, cognitive presence, and social presence) and how these presences interact in providing an educational experience in online and blended learning environments. This meta-analysis examined 19 empirical studies on the CoI Presences (Teaching Presence, Social Presence, and Cognitive Presence) and their correlations with learning outcomes, including actual learning, perceived learning, and satisfaction. It was found that teaching presence and actual learning were moderately positively correlated, (r = .353). There was a weak correlation between cognitive presence and actual learning, (r = .250) and social presence and actual learning, (r = .199). For the correlation between the presences and perceived learning, cognitive presence and perceived learning was found to be strongly correlated, (r = .663), followed by the moderate correlation between social presence and perceived learning (r = .432), and teaching presence and perceived learning, (r = .392). With respect to satisfaction, the correlation between cognitive presence and satisfaction, (r = .586) and between teaching presence and satisfaction was strong, (r = .510), but the correlation between social presence and satisfaction was moderate, (r = .447). The findings have implications for designers and instructors who design and teach online and blended courses to include these presences. (more…)