This study investigated how gender and beliefs about ability moderate the effects of attributional praise feedback on college students’ task motivation and performance in an online environment. We conducted a 3 (praise type: ability vs. effort vs. none) × 2 (gender: male vs. female) × 2 (belief about ability: entity vs. incremental) between-subjects factorial experiment with 196 college students. Analysis of variance of the data detected significant interactions between praise and gender on the main outcome variables. Overall, praise feedback had significantly positive impact on male participants’ task performance, self-efficacy, and intrinsic motivation; whereas for female participants, praise feedback had no significant effects on these variables. Additionally, there is a trend (albeit non-significant) interaction between praise type and belief type on task effort, indicating that for entity-belief group, ability praise feedback tended to positively influence task effort whereas for incremental-belief group, effort praise feedback tended to positively impact task effort. Implications of these findings for theory and practice are discussed.
Digital badges, widely known as alternative or micro-credentials, have gained increasing recognition in recent years as innovative pedagogical tools in higher education. Despite many anecdotal and conceptual statements of value, the effectiveness of using digital badges to improve learning performance is still largely unknown. This study addressed this gap by investigating the impact of these badges with added instructional scaffolding on pre-service teachers’ perceived technology capabilities and their actual learning performance while studying within a large undergraduate technology integration course. Compared with similar participants who experienced traditional instructional projects instead of the badges, those learning with digital badges not only reported higher levels of perceived confidence in their technology integration skills but also achieved higher levels of course assignment and overall course grades. Conclusions from this study offered ways to improve learning performance with the support of digital badge technology and drew implications for future scholarship in this area.
A cyber-flipped course was conducted with the flipped classroom pedagogy by using a wholly online approach for all learning activities in asynchronous and synchronous class sessions. Literature suggests that traditional flipped courses can effectively enhance students’ learning outcomes in comparison to non-flipped courses. However, conducting all asynchronous and synchronous learning activities using a wholly online approach has not been reported. This paper aimed to investigate how student engagement in four different types of learning activities affects their learning outcomes in a cyber-flipped course. Results show that the learning activities with the flipped classroom pedagogy can be successfully implemented and conducted in a wholly online course along with time and space flexibility for learners. This study also found that students who watched more pre-recorded video lectures tended to participate in the synchronous learning activities more actively and obtained a higher semester grade; higher completion of asynchronous learning activities had benefited students’ understanding of the learning concepts. Furthermore, students who had a high level of readiness by attending synchronous class sessions on time and keeping their webcams activated had more frequent and proactive interactions with their peers and instructor.
The recent movement to integrate the flipped classroom model into higher education has resulted in significant changes that affected both teaching and learning practices in different ways. After almost a decade of research on the flipped classroom model, different emergent outcomes have been reported in a domain specific context. To gain a comprehensive understanding of the flipped classroom implementation in a university context, a review of the literature on the use of flipped classroom in a university context was conducted. This study was guided by interpreting the previous research findings according to the domain of utilization, opportunities, challenges, and extensions to the conventional flipped classroom model. This study found that the utilization of flipped classroom in various disciplines is mainly advocated to promote students’ engagement, metacognition, attitude, performance, understanding, and achievement, as well as other learning outcomes. The key challenges of this method, shared across all disciplines, were devoted to the length of the video/digital materials and time required for instructors to prepare the learning materials and for students to master it. Recommendations for policy makers and other crucial insights for the future studies were highlighted.
Multitasking refers to the simultaneous execution of two or more tasks. Perceived multitasking superiority of the digital natives and gifted students in the popular education literature need to be investigated with robust studies. In this regard, the effect of different multitasking scenarios on multimedia learning was investigated with 93 gifted and 121 non-gifted middle school students. The respondents were assigned randomly to three different scenarios: Monotasking (i.e. watching an instructional video without interruption), concurrent multitasking (i.e. texting during an instructional video) and sequential multitasking (i.e. watching instructional and distractive videos successively). In addition to content learning, the students’ scores on topic interest, daily multitasking habits, subjective cognitive load and working memory capacity were considered. Working memory capacity correlated positively with learning outcomes. After it was included as a covariate, the results of a two-way between-groups ANCOVA revealed that multitasking conditions interfered with learning. Gifted students were consistently more successful than non-gifted students, but suffered during concurrent multitasking. Therefore, organizing instructional interventions according to an empirically questionable multitasking superiority seems problematic.
Adaptive learning systems need large pools of examples for practice—thousands of items that need to be organized into hundreds of knowledge components within a domain model. Domain modeling and closely related student modeling are intensively studied in research studies. However, there is a gap between research studies and practical issues faced by developers of scalable educational technologies. The aim of this paper is to bridge this gap by connecting techniques and notions used in research papers to practical problems in development. We put specific emphasis on scalability—on techniques that enable relatively cheap and fast development of adaptive learning systems. We summarize conceptual questions in domain modeling, provide an overview of approaches in the research literature, and discuss insights based on the development and analysis of a widely used system. We conclude with recommendations for both developers and researchers in the area of adaptive learning systems.
This study aimed to classify latent profiles of Korean undergraduates’ academic emotions in an e-learning environment, and to examine the effects of instructional variables on these profiles as well as the differences in their learning outcomes. A survey was conducted among 777 students who participated in online courses offered by a Korean university. Latent profile analysis revealed four types of emotional profiles: a moderate type (MT); a positive type (PT); a negative type (NT); and an ambivalent type (AT). MT comprised 72.5% of the total number of participants and showed medium levels of both positive emotions (PE) and negative emotions (NE). PT comprised 13.1% of the participants and showed high levels of PE and low levels of NE. NT comprised 10.2% of the participants and showed low levels of PE and high levels of NE. AT comprised 4.2% of the participants and both showed high levels of both PE and NE. Further analysis showed that the quality of instructional content, interaction, the system, and evaluation all proved to be predictors of emotional profiles. Moreover, they indicated differences in perceived achievement and in learner satisfaction. Based on these results, this study provides a discussion and suggestions for further studies.
This mixed methods study is aimed to examine the feasibility of integrating mathematical problem solving with architectural design via a 3D epistemic simulation game to promote active mathematics learning for middle-school students. The experimental-control pretest/posttest group design was adopted to examine whether the experience of interacting with an architecture simulation game would improve students’ math knowledge for and performance of problem solving. Data were collected from 61 6th graders via both quantitative and qualitative methods, including math problem-solving and mental rotation tests, video- and screen-capture of game play behaviors, observation, as well as game logs. The study results indicated that the gaming group performed significantly better than the non-gaming control group in the math context problem solving test. The infield observation and participants’ gaming behavior analysis suggested that the learning and practice of mathematical problem solving during gaming is a cognizant and planned endeavor framed by carefully designed game actions and objects.
Improving teacher professional development for online and blended learning: a systematic meta-aggregative review
In order to fully realise the potential of online and blended learning (OBL), teacher professional development (TPD) strategies on how to teach in an online or blended learning environment are needed. While many studies examine the effects of TPD strategies, fewer studies target the specific important components of these strategies. This study addresses that gap by conducting a systematic review of qualitative data consisting of 15 articles on TPD that targets OBL. Using a meta-aggregative approach, six different synthesised findings were identified and integrated into a visual framework of the key components of TPD for OBL. These synthesised findings are the base for the action recommendations which present specific and contextualised suggestions. Taken together, the findings can inform in-service teachers and trainers, together with further research and development efforts that are concerned with TPD for OBL.
In this critical literature review, we seek to understand why multidimensional, psychological measures of human emotion that have been popular in the study of emotion and learning to date, may not yield the statistical power or construct validity necessary to consistently explain or predict human learning. We compare competing theories and conclude that educational studies tend towards use of multi-dimensional models of human emotions which, while useful in educational psychology and therapeutic practice, suffer from psychometric flaws and generate lower power when used as empirical research constructs compared with the “basic emotion” models and their derivatives popular in the neurobiological, cognitive, and social sciences. Based on our review, we conclude that more extensive use of physiological measures and analysis of spontaneous emotion language, both rooted in the basic emotions tradition rather than continued psychological measurement of multi-dimensional emotions, may yield more consistent and significant results and reduce education researchers’ reliance on self-report measures. Findings from the review may advance the selection of operational definitions and formulation of research questions for new empirical studies of the intersections between emotion and learning.
Development of a computer-assisted Japanese functional expression learning system for Chinese-speaking learners
Because a large number of Chinese characters are commonly used in both Japanese and Chinese, Chinese-speaking learners of Japanese as a second language (JSL) find it more challenging to learn Japanese functional expressions than to learn other Japanese vocabulary. To address this challenge, we have developed Jastudy, a computer-assisted language learning (CALL) system designed specifically for Chinese-speaking learners studying Japanese functional expressions. Given a Japanese sentence as an input, the system automatically detects Japanese functional expressions using a character-based bidirectional long short-term memory with a conditional random field (BiLSTM-CRF) model. The sentence is then segmented and the parts of speech (POS) are tagged (word segmentation and POS tagging) by a Japanese morphological analyzer, MeCab (http://taku910.github.io/mecab/), trained using a CRF model. In addition, the system provides JSL learners with appropriate example sentences that illustrate Japanese functional expressions. The system uses a ranking system, which gives easier sentences a higher rank, when selecting example sentences. A support vector machine for ranking (SVMRank) algorithm estimates the readability of example sentences, using Japanese-Chinese common words as an important feature. A k-means clustering algorithm is used to cluster example sentences that contain functional expressions with the same meanings, based on part-of-speech, conjugation form, and semantic attributes. Finally, to evaluate the usefulness of the system, we have conducted experiments and reported on a preliminary user study involving Chinese-speaking JSL learners.
Building a game-enhanced formative assessment to gather evidence about middle school students’ argumentation skills
In this paper, we describe an effort to develop and evaluate an innovative formative assessment to gather evidence about middle school students’ argumentation skills. Specifically, this game-enhanced scenario-based assessment (Seaball—Semester at Sea) includes a series of argumentative reasoning activities in the context of an extended scenario wherein students debate the issue of whether junk food should be sold to students. These activities were designed around argumentation learning progressions (i.e., hypotheses about the qualitative shifts that occur as students achieve higher levels of sophistication in argumentation) which serve as a framework to determine the targeted skills, levels and activity sequences. Performance feedback is also provided in the assessment. We conducted a pilot study, aimed at examining student performance and the validity of the tasks as a measure of argumentation skills. More than 100 middle school students completed this assessment and additional external measures of argumentation in a pre/post design. Descriptive statistics of student performance in the activities, analyses of item difficulty, and correlations are reported. Results indicated that students’ total scores were significantly correlated with external measures of argumentation skills, and with students’ state reading and writing test scores. In addition, students achieved higher average scores in a post-test of argumentation skills after having completed the Seaball activities. Finally, explanatory feedback about students’ task performance was found to be beneficial to those who were “Below” or “Approaching” proficient on the state reading and writing test. We conclude with implications for assessment design and instruction in argumentation.
The field of adaptive e-learning is continuously developing. More research is being conducted in this area as adaptive e-learning aims to provide learners with adaptive learning paths and content, according to their individual characteristics and needs, which makes e-learning more efficient and effective. The learner model, which is a representation of different learner’s characteristics, plays a key role in this adaptation. This paper presents a systematic literature review about learner modelling during the last 5 years, describing the different modelled characteristics and the adopted modelling techniques and modeling types: automatic modeling and collaborative modeling. 107 publications were selected and analyzed, and six categories of the modelled characteristics were identified. This literature review contributes to the identification of the learners’ individual traits and presents the most used modelling techniques for each of them. It also identifies the latest research trends of Learner Modeling and generates future research directions in this field.
Teachers’ perceptions of the usability of learning analytics reports in a flipped university course: when and how does information become actionable knowledge?
The flipped classroom model is a form of blended learning in which delivery of content occurs with online materials, and face-to-face meetings are used for teacher-guided practice. It is important that teachers stay up to date with the activities students engage in, which may be accomplished with the help of learning analytics (LA). This study investigated university teachers’ perceptions of whether weekly LA reports that summarized student activities supported their teaching activities (n = 7). The teachers reported using the LA reports for diagnosing and intervening during student activities, and that the reports encouraged them to start interaction with students. Teachers did sometimes find it difficult to connect the information from the LA reports to concrete interventions, which was partly dependent on the level of the teacher’s experience. LA reports might support teachers further by not only offering information, but also by suggesting interventions.
Correction to: Cultural divides in acceptance and continuance of learning management system use: a longitudinal study of teenagers
In the abstract, the second “FG” in the sentence below should be “SG”:
The sample was classified into three cultural groups: 203 first-generation immigrant students (FG), 354 second-generation immigrant students (FG), and 521 non-immigrant student (Native).
Thus, the original sentence should be corrected as follows:
The sample was classified into three cultural groups: 203 first-generation immigrant students (FG), 354 second-generation immigrant students (SG), and 521 non-immigrant student (Native).
A review of empirical studies of affordances and development of a framework for educational adoption of mobile social media
As one of the most widely adopted mobile and social media applications, Tencent WeChat ® (‘WeChat’) has been increasingly used in education at all levels in Asia, and in China in particular. However, only a small number of studies have been conducted to explore educational affordances of WeChat. In this paper, these affordances are defined as opportunities for an educational activity that are determined and supported by perceived and actual features of a technology tool or an environment (Gibson in The ecological approach to visual perception, Houghton Mifflin, Boston, 1979; Norman in The psychology of everyday things, Basic Books, New York, 1988; Sanders in Ecol Psychol 9(1):97–112, 1997). The authors conducted a review of 21 studies out of a pool of 1984 identified publications on the topic to examine existing practices, empirical studies and recommendations for the uses of WeChat, and with the over-reaching aim of articulating a framework for the adoption of educational affordances of mobile social media. Such framework will serve practice as well as research on educational uses of mobile social media and help extend theory of affordances in this domain. A total of seven categories of educational affordances of WeChat were explicated and included in this framework: Resources Sharing, Authentic Learning, Collaboration, Community Building, Motivating Environment, Evaluation and Feedback, and Administration for Learning. Guidelines for the adoption of this framework are developed, and suggestions for future research are proposed.
Development of software to support argumentative reading and writing by means of creating a graphic organizer from an electronic text
This paper describes the development of a software program that supports argumentative reading and writing, especially for novice students. The software helps readers create a graphic organizer from the text as a knowledge map while they are reading and use their prior knowledge to build their own opinion as new information while they think about writing their essays. Readers using this software can read a text, underline important words or sentences, pick up and dynamically cite the underlined portions of the text onto a knowledge map as quotation nodes, illustrate a knowledge map by linking the nodes, and later write their opinion as an essay while viewing the knowledge map; thus, the software bridges argumentative reading and writing. Sixty-three freshman and sophomore students with no prior argumentative reading and writing education participated in a design case study to evaluate the software in classrooms. Thirty-four students were assigned to a class in which each student developed a knowledge map after underlining and/or highlighting a text with the software, while twenty-nine students were assigned to a class in which they simply wrote their essays after underlining and/or highlighting the text without creating knowledge maps. After receiving an instruction regarding a simplified Toulmin’s model followed by instructions for the software usage in argumentative reading and writing along with reading one training text, the students read the target text and developed their essays. The results revealed that students who drew a knowledge map based on the underlining and/or highlighting of the target text developed more argumentative essays than those who did not draw maps. Further analyses revealed that developing knowledge maps fostered an ability to capture the target text’s argument, and linking students’ ideas to the text’s argument directly on the knowledge map helped students develop more constructive essays. Accordingly, we discussed additional necessary scaffolds, such as automatic argument detection and collaborative learning functions, for improving the students’ use of appropriate reading and writing strategies.
In an effort to create meaningful user experiences, instructional designers participate in continuous projection and reflection during design. Empathic design draws on instructional designers’ sensitivity toward their learners as a reference for design. Empathic forecasting, or predictions about an emotional reaction to future events, is an important influence on design in general and may be particularly meaningful for empathic design. This exploratory mixed-methods study examined how instructional designers’ imagined the cognitive and emotional learner experience as they designed a collaboration-based interactive case study to promote interaction and collaboration among physicians, radiobiologists, and radiation physicists. We employed a protocol analysis methodology to document the verbal exchanges of members of this design team during collaborative meetings. Online surveys that included scale-based ratings and short open-ended questions assessed learners’ perceptions of their instructional experience. Findings indicate that instructional designers visualized learner interaction with the Virtual Hospital, and emoted learner feelings with the activity while engaging in design. User results indicate that the outcome the instructional designers envisioned for the user experience aligned with user perceptions of their experiences during the activity.
A large-scale implementation of predictive learning analytics in higher education: the teachers’ role and perspective
By collecting longitudinal learner and learning data from a range of resources, predictive learning analytics (PLA) are used to identify learners who may not complete a course, typically described as being at risk. Mixed effects are observed as to how teachers perceive, use, and interpret PLA data, necessitating further research in this direction. The aim of this study is to evaluate whether providing teachers in a distance learning higher education institution with PLA data predicts students’ performance and empowers teachers to identify and assist students at risk. Using principles of Technology Acceptance and Academic Resistance models, a university-wide, multi-methods study with 59 teachers, nine courses, and 1325 students revealed that teachers can positively affect students’ performance when engaged with PLA. Follow-up semi-structured interviews illuminated teachers’ actual uses of the predictive data and revealed its impact on teaching practices and intervention strategies to support students at risk.