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Threshold concepts are transformative elements of domain knowledge that enable those who attain them to engage domain tasks in a more sophisticated way. Existing research tends to focus on the identification of threshold concepts within undergraduate curricula as challenging concepts that prevent attainment of subsequent content until mastered. Recently, threshold concepts have likewise become a research focus at the level of doctoral studies. However, such research faces several limitations. First, the generalizability of findings in past research has been limited due to the relatively small numbers of participants in available studies. Second, it is not clear which specific skills are contingent upon mastery of identified threshold concepts, making it difficult to identify appropriate times for possible intervention. Third, threshold concepts observed across disciplines may or may not mask important nuances that apply within specific disciplinary contexts. The current study therefore employs a novel Bayesian knowledge tracing (BKT) approach to identify possible threshold concepts using a large data set from the biological sciences. Using rubric-scored samples of doctoral students' sole-authored scholarly writing, we apply BKT as a strategy to identify potential threshold concepts by examining the ability of performance scores for specific research skills to predict score gains on other research skills. Findings demonstrate the effectiveness of this strategy, as well as convergence between results of the current study and more conventional, qualitative results identifying threshold concepts at the doctoral level.

Science students frequently struggle to apply crosscutting concepts such as scale or rates of change, and do not always effectively differentiate between linear and nonlinear processes. We approach this challenge from an embodied cognition perspective, which suggests learning can be facilitated by engaging students in physical activities that are aligned with target concepts. This article describes two experiments where participants learned about exponential scales applied to measuring earthquakes (Richter scale) and the strength of acids/bases (pH scale). Whether participants engaged with an embodied simulation or used traditional instructional media for none, one, or both of these topics was manipulated across the two experiments. Experiment 1 recruited high school-aged participants and Experiment 2 recruited non-STEM undergraduate majors. Results from the experiments showed that using the embodied simulation led to greater declarative knowledge gains for the earthquake topic but not for acids/bases. Learning gains for the crosscutting concept (exponential growth) were higher for the embodied simulation participants on both topics. Especially notable was the finding that learning the crosscutting concept from an embodied simulation in one domain transferred to a second domain where the same concept was relevant. We discuss implications for applications of embodied cognition to the design of learning environments and to interventions that support learning transfer.

An open-ended serious game can engage students' scientific problem-solving processes. However, understanding how students learn higher-order thinking skills through solving a problem in an open-ended game system is a challenge. The complex game systems may make learning more difficult for students with different characteristics such as an at-risk label. Recent research stresses the importance of using gameplay data to better understand diverse individuals' learning behaviors and performances in the context of serious games. We analyzed gameplay data of a serious game called "Alien Rescue" to identify navigation behavior patterns between at-risk and non-at-risk middle school students. Particularly, we incorporated the combination of lag sequential analysis and sequential pattern mining in statistical analyses. The results revealed that the non-at-risk and at-risk students used problem-solving strategies differently when they navigated the environment. The findings using this integrated method confirmed that additional support was needed for at-risk students in order for them to develop contextual and procedural knowledge for problem-solving in the game environment. The findings provide methodological guidelines for researchers considering a sequential analysis as well as offer practical guidelines for game designers to consider when designing serious games with a complex problem so as to help at-risk students.

Objective: The aim of this current paper is to investigate the salient embodiment features in the empirical studies on technology-enabled embodied learning environments (TEELEs), and to contribute a comprehensive conceptual framework to direct the understanding and the designing of TEELEs -- to embody and how to embody. Method: In this thematic paper, we carefully selected and reviewed 28 empirical studies (peer-reviewed journal articles published in the recent decade between 2010 and 2020) on TEELEs, and analyzed their salient features concerning embodiment. Results and Implications: Synthesizing the characteristics distilled from the selected studies, we propose the conceptual framework of embodied immersion, which consists of three major dimensions, namely, physical, sensory, and cognitive immersions. Eight factors -- means of embodiment, amount of motoric movements, point of view, media effects, haptic effects, operational congruency, learning congruency, and personalization -- contribute to these three dimensions, and are carefully articulated, discussed, and explicated. The discussions around the embodied immersion framework are rooted in the concepts of presence, immersion, and agency. We regard our framework as a trinity borrowing the ingredients from each of those three that will guide through the understanding and the designing of TEELEs.

Guided by theories of socialization and possible selves, this study examines how STEM doctoral students perceive their academic and professional trajectories. More specifically, we rely on four years of interview data from 66 doctoral students in the biological sciences to explore students' perceived trajectories, focusing on the salient identities and experiences that shape the way students identify and describe their graduate experiences over time. Findings reveal wide variation in terms of how students described their trajectories, with some students describing linear trajectories and/or unchanging career interests, while others described their developmental trajectories as highly turbulent and non-linear. These perceived trajectories were largely shaped by student-advisor interactions, the value students placed on becoming "independent" scientists, and the privilege students brought with them to their graduate programs.

Recent research has emphasized the importance of leveraging embodied interactions for learning critical STEM concepts. ELASTIC3S--an embodied environment for learning about cross-cutting concepts (i.e., non-linear growth)--allows learners to interact with different science simulations through whole-body gestures. Technological advances in gesture recognition can track and respond to students' gestures, however, there has been little investigation into how the gestures performed in these environments relate to subsequent learning. The need for sequential pattern recognition methods is critical in embodied learning if we are to understand how gestural interaction with a simulation facilitates learning. Using data collected via Microsoft Kinect V2 from twelve college students, we applied multivariate Dynamic Time Warping for clustering to identify gestural patterns in ELASTIC[superscript 3]S as evidence for embodied learning processes. Our findings showed that identified trends of simulation use were indicative of students' struggles to understand the underlying ideas or use of the system and were associated with learning performance. These indicators can potentially be used to leverage real time, in-simulation assistance and promote a more adaptive learning experience via embodied simulations.

Research from brain science and the learning sciences support the notion that human cognition is grounded in our sensorimotor engagement with the physical world and that processes of learning can be shaped by our movements and actions. Increasing recognition that effective educational interventions can be seeded with embodied actions is paralleled by recent and rapid advances in sensing and motion capture technologies. These advances allow for a new wave of cyberlearning environments that permit learners to use their bodies to create and manipulate digital representations of core ideas in a variety of learning domains. Drawing on the research literature on embodied cognition and design principles for creating effective embodied educational simulations, we present the design of a cyberlearning platform called ELASTIC3S. We describe the design rationale and preliminary data from a small empirical study of the ELASTIC3S platform that address the potential for enhancing science, technology, engineering, and mathematics (STEM) learning and engagement through embodied interaction.

There is much enthusiasm in higher education about the benefits of adaptive learning and using big data to investigate learning processes to make data-informed educational decisions. The benefits of adaptive learning to achieve personalized learning are obvious. Yet, there lacks evidence-based research to understand how data such as user behavior patterns can be used to design effective adaptive learning systems. The purpose of this study, therefore, is to investigate what behavior patterns learners with different characteristics demonstrate when they interact with an adaptive learning environment. Incoming 1st-year students in a pharmacy professional degree program engaged in an adaptive learning intervention that aimed to provide remedial instruction to better prepare these professional students before they began their formal degree program. We analyzed the participants' behavior patterns through the usage data to understand how they used the adaptive system based upon their needs and interests. Using both statistical analyses and data visualization techniques, this study found: (1) apart from learners' cognitive ability, it is important to consider affective factors such as motivation in adaptive learning, (2) lack of alignment among various components in an adaptive system can impact how learners accessed the system and, more importantly, their performance, and (3) visualizations can reveal interesting findings that can be missed otherwise. Such research should provide much needed empirical evidences and useful insights about how the analytics can inform the effective designs of adaptive learning.

Using a multi-case approach, we examined students' behavior patterns in interacting with a serious game environment using the emerging technologies of learning analytics and data visualization in order to understand how the patterns may vary according to students' learning characteristics. The results confirmed some preliminary findings from our previous research, but also revealed patterns that would not be easily detected without data visualizations. Such findings provided insights about designing effective learning scaffolds to support the development of problem-solving skills in young learners and will guide our next-step research.

In this study, the researchers examined if and to what extent social media tools such as Facebook and Twitter can augment participants' learning experience in an xMOOC and offer an additional social space. Two research questions guided this inquiry: (1) What did MOOC participants consider the usefulness of the Facebook group and Twitter feed associated with their MOOC course? and (2) How did the participants use the Facebook group and Twitter feed associated with their MOOC course? The findings from participants' perceptions and usage using both quantitative and qualitative data indicated that the additional social space provided by the two social media tools can augment the learning experience by providing an environment to share resources, connect with others, enhance communications, and provide a space to post personal feelings or reflections of learning in an informal and quick manner. However, the findings did not provide strong evidence to indicate any deeper interactions beyond these uses. The results highlighted the importance of mediation and scaffolding from instructors in using social media tools in order to help connect learners in large online courses such as MOOCs.

While there is evidence of the growing popularity of iPads and other tablets in K-12 education, little is understood about how teachers use these devices in their instruction. This study examines 342 teachers' comfort level with and perception toward iPad use and any changes that occurred over the implementation year. Using a mixed-methods design, this study found significant differences in comfort level by years of teaching and school levels. Female teachers, teachers with 20 years or less of teaching experience, and elementary school teachers were more positive about their perception toward iPad use than the other groups. High school teachers' perception was the lowest overall. Analyses of teacher interviews revealed affordances, challenges, and diverse ways of how teachers used iPads in their instruction. Implications for practice and research are discussed.

Given the growing popularity of digital games as a form of entertainment, educators are interested in exploring using digital games as a tool to facilitate learning. In this study, we examine game-based learning by describing a learning environment that combines game elements, play, and authenticity in the real world for the purpose of engaging students' learning of science and enhancing student motivation. We discuss the design of the environment and present research conducted. Our findings demonstrate that the design of an engaging, interactive environment using a game-based approach can help students have fun while learning.

This study examined participants' learning experiences in the context of a six-week massive open online course (MOOC) in journalism with five thousand students from 137 countries. Three research questions were asked: (1) Who are the students and why are they enrolled in this MOOC?, (2) How much time have the students spent in taking this MOOC and have they completed all the assignments?, and, (3) What have they learned and what aspects of this MOOC do the students find most helpful? Four hundred and nine students responded to a survey and forty-four responded to interview questions. The main findings showed 84% of the participants were working professionals and only 28.9% were from a journalism background. Of those who did not complete the course, lack of time was the top reason. Most participants reported a positive learning experience, but lack of feedback and/or poor quality were reported as negative experiences. The discussion forum was the least liked aspect of the course.