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1.
To better understand the relationship between enjoyment and boredom and students' use of cognitive learning strategies, we analyzed both directions of effects between these constructs as described in the control-value theory of achievement emotions (Pekrun, 2006; 2018). Our study used a sequential design in which students' (N = 338 4th grade students) effective use of cognitive learning strategies was measured in real learning situations, allowing insights into the temporal order of effects and discrimination between intra- and interindividual effects (N = 8020 assessments within students). An increased intraindividual level of enjoyment positively predicted subsequent effective use of learning strategies, whereas effective use of learning strategies did not predict students’ subsequent enjoyment on the intraindividual level. Interindividual differences in enjoyment and effective use of cognitive learning strategies were unrelated, whereas negative relations were found for boredom and effective strategy use. On the intraindividual level, boredom and effective strategy use were unrelated. 相似文献
2.
Penelope J. Standen David J. Brown Mohammad Taheri Maria J. Galvez Trigo Helen Boulton Andrew Burton Madeline J. Hallewell James G. Lathe Nicholas Shopland Maria A. Blanco Gonzalez Gosia M. Kwiatkowska Elena Milli Stefano Cobello Annaleda Mazzucato Marco Traversi Enrique Hortal 《British journal of educational technology : journal of the Council for Educational Technology》2020,51(5):1748-1765
Artificial intelligence tools for education (AIEd) have been used to automate the provision of learning support to mainstream learners. One of the most innovative approaches in this field is the use of data and machine learning for the detection of a student’s affective state, to move them out of negative states that inhibit learning, into positive states such as engagement. In spite of their obvious potential to provide the personalisation that would give extra support for learners with intellectual disabilities, little work on AIEd systems that utilise affect recognition currently addresses this group. Our system used multimodal sensor data and machine learning to first identify three affective states linked to learning (engagement, frustration, boredom) and second determine the presentation of learning content so that the learner is maintained in an optimal affective state and rate of learning is maximised. To evaluate this adaptive learning system, 67 participants aged between 6 and 18 years acting as their own control took part in a series of sessions using the system. Sessions alternated between using the system with both affect detection and learning achievement to drive the selection of learning content (intervention) and using learning achievement alone (control) to drive the selection of learning content. Lack of boredom was the state with the strongest link to achievement, with both frustration and engagement positively related to achievement. There was significantly more engagement and less boredom in intervention than control sessions, but no significant difference in achievement. These results suggest that engagement does increase when activities are tailored to the personal needs and emotional state of the learner and that the system was promoting affective states that in turn promote learning. However, longer exposure is necessary to determine the effect on learning. 相似文献
3.
This study evaluated students' affective learning in an introductory computing course that was taught in Hong Kong once in a lecture format and twice in a rich interactive multimedia online format to 414 college students in all. A simplified experience sampling method was used to assess affective learning at the midterm and end of each course in terms of intrinsic engagement (positive affect, perceived challenges, perceived skills in course activities), extrinsic engagement (performance expectations, performance goals, performance self‐efficacy), and negative affect in course activities. Controlling for students' computing background and pre‐enrollment academic ability, multivariate analysis of covariance indicated that, compared to lectures, e‐learning modules fostered more intrinsic engagement, comparable extrinsic engagement, and more negative affect. Findings suggest directions for developing online courses that optimise both cognitive learning and affective learning. 相似文献
4.
Understanding emotions in technology-based learning environments (TBLEs) has become a paramount goal across different research communities, but to date, these have operated in relative isolation. Based on control-value theory (Pekrun, 2006), we reviewed 186 studies examining emotions in TBLEs that were published between 1965 and 2018. We extracted effect sizes quantifying relations between emotions (enjoyment, curiosity/interest, anxiety, anger/frustration, confusion, boredom) and their antecedents (control-value appraisals, prior knowledge, gender, TBLE characteristics) and outcomes (engagement, learning strategies, achievement). Mean effects largely supported hypotheses (e.g., positive relations between enjoyment and appraisals, achievement, and cognitive support) and remained relatively stable across moderators. These findings imply that levels of emotions differ across TBLEs, but that their functional relations with appraisals and learning are equivalent across environments. Implications for research and designing emotionally sound TBLEs are discussed. 相似文献
5.
Gwen Noteborn Katerina Bohle Carbonell Amber Dailey-Hebert Wim Gijselaers 《The Internet and Higher Education》2012,15(3):176-183
This paper analyzed the role of emotions in a virtual world (Second Life) through students' level of enjoyment and boredom and their influence on students' achievement level. The virtual world was an educational tool used to fully immerse students in the content of the course. In addition to supporting prior research on the importance of task value on academic enjoyment, the current research provides a new perspective on the relationship between academic emotions and academic success, particularly for virtual worlds. A regression analysis was conducted to measure the relationship of task value and emotions on two types of academic performance: Individual exam scores and team scores on their Second Life assignment. Pekrun's Academic Emotions Questionnaire (AEQ) was used to measure two academic emotions: boredom and enjoyment. Both academic emotions were measured on an individual level. Results from this study show that task value was positively related to enjoyment and negatively related to boredom, yet it was unrelated to academic performance. While enjoyment had a positive relationship to exam performance, boredom also had a positive relationship to the team assignment conducted in the virtual world. The possibility that students might have answered the AEQ relating to the theoretical aspects of the course instead of the practical aspects of the Second Life Assignment, may be one possible explanation for this result. 相似文献
6.
We propose a theoretical model linking students' epistemic beliefs, epistemic emotions, learning strategies, and learning outcomes. The model was tested across two studies with 439 post-secondary students from Canada, the United States, and Germany for Study 1, and 56 students from Canada for Study 2. For Study 1, students self-reported their epistemic beliefs about climate change, read four conflicting documents about the causes and consequences of climate change, self-reported their epistemic emotions and learning strategies used to learn the content, and were given an inference verification test to measure learning. Study 2 used the same procedure but added a think aloud protocol to capture self-regulatory processes and emotions as they occurred. Path analyses revealed that epistemic beliefs served as important antecedents to the epistemic emotions students experienced during learning. Students who believed that the justification of knowledge about climate change requires critical evaluation of multiple sources experienced higher levels of enjoyment and curiosity, and lower levels of boredom when confronted with conflicting information. A belief in the complexity of this knowledge was related to lower levels of confusion, anxiety, and boredom. A belief in the uncertainty of this knowledge predicted lower levels of anxiety and frustration, and a belief in the active construction of knowledge predicted lower levels of confusion. Epistemic emotions predicted the types of learning strategies students used to learn the content and mediated relations between epistemic beliefs and learning strategies. Learning strategies predicted learning outcomes and mediated relations between epistemic emotions and learning outcomes. Implications for research on epistemic beliefs, epistemic emotions, and students' self-regulated learning are discussed. 相似文献
7.
Scotty Craig Arthur Graesser Jeremiah Sullins Barry Gholson 《Learning, Media and Technology》2004,29(3):241-250
The role that affective states play in learning was investigated from the perspective of a constructivist learning framework. We observed six different affect states (frustration, boredom, flow, confusion, eureka and neutral) that potentially occur during the process of learning introductory computer literacy with AutoTutor, an intelligent tutoring system with tutorial dialogue in natural language. Observational analyses revealed significant relationships between learning and the affective states of boredom, flow and confusion. The positive correlation between confusion and learning is consistent with a model that assumes that cognitive disequilibrium is one precursor to deep learning. The findings that learning correlates negatively with boredom and positively with flow are consistent with predictions from Csikszentmihalyi's analysis of flow experiences. 相似文献
8.
Online learning continues to grow, but there is limited empirical research on the personal factors that influence success in online contexts. This investigation addresses this research gap by exploring the relations between several discrete achievement-related emotions (boredom, frustration, and enjoyment) and self-regulated learning behaviors (elaboration and metacognition) in an online course. Results from a survey of 302 undergraduates participating in an online course indicated that enjoyment, a positive activating emotion, was a positive predictor of elaboration and metacognition. Moreover, consistent with previous findings from a similar sample, frustration, a negative activating emotion, emerged as a positive predictor of metacognition. Implications for the theory, research, and practice of online learning are discussed, as are theoretical implications for understanding students' achievement emotions and self-regulated learning behaviors. 相似文献
9.
Academic emotions have largely been neglected by educational psychology, with the exception of test anxiety. In 5 qualitative studies, it was found that students experience a rich diversity of emotions in academic settings. Anxiety was reported most often, but overall, positive emotions were described no less frequently than negative emotions. Based on the studies in this article, taxonomies of different academic emotions and a self-report instrument measuring students' enjoyment, hope, pride, relief, anger, anxiety, shame, hopelessness, and boredom (Academic Emotions Questionnaire [AEQ]) were developed. Using the AEQ, assumptions of a cognitive-motivational model of the achievement effects of emotions, and of a control/value theory of their antecedents (Pekrun, 1992b, 2000), were tested in 7 cross-sectional, 3 longitudinal, and 1 diary study using samples of university and school students. Results showed that academic emotions are significantly related to students' motivation, learning strategies, cognitive resources, self-regulation, and academic achievement, as well as to personality and classroom antecedents. The findings indicate that affective research in educational psychology should acknowledge emotional diversity in academic settings by addressing the full range of emotions experienced by students at school and university. 相似文献
10.
Technology-rich learning environments (TREs) play an increasingly important role for 21st century education, and the emotions learners experience in these environments are pivotal for their cognitive and affective learning gains. The contributors to this special issue address the importance of understanding and measuring emotions in TREs as a mechanism for fostering learning. In particular, the special issue situates this research with a systemic review and meta-analysis of the literature on emotions in TREs. Following this review empirical research is presented on measuring emotions in the context of learning with TREs in multiple domains, including medicine, history, and mathematics. These researchers use concurrent measures to capture students’ cognitive, metacognitive and affective processes before, during, and after solving problems, documenting the complex role of such processes as individuals and groups learn with technology. The special issue concludes with two commentaries that point the way to next steps in this field of research. 相似文献
11.
This study investigated the relationships of students’ incremental beliefs of math ability to their achievement emotions, classroom engagement and math achievement. A sample of 273 secondary students in Singapore were administered measures of incremental beliefs of math ability, math enjoyment, pride, boredom and anxiety, as well as math classroom attention and disruption. In addition, students’ end-of-year math achievement scores were collected from school records. The hypothesised mediation model was supported in structural equation modelling analysis. Incremental beliefs of math ability were associated positively with math enjoyment and pride, and negatively with math boredom and anxiety. Achievement emotions fully mediated the relationships of incremental beliefs of math ability to classroom engagement and math achievement. Incremental beliefs of math ability were associated positively with classroom attention through math enjoyment and pride, negatively with classroom disruption through math anxiety and positively with math achievement through the two outcome-related emotions, math pride and anxiety. The findings and implications are discussed in the academic context of Singapore. 相似文献
12.
Over the last years there has been a growing use of 3D virtual environments for educational purposes. Many studies advocate the integration of these environments in the daily teaching practice of various subjects. This requires innovative design in order create the appropriate affective/ pedagogical conditions as well as the development and use of well-structured activities in order to achieve effective collaborative learning. This paper presents an exploratory study in which collaborative learning strategies and cognitive apprenticeship models act as the pedagogical framework to facilitate learning and collaboration. The context is the teaching of mathematics in primary education via a 3D virtual environment. Specifically, we focus on evaluating students’ engagement (behavioral, affective and cognitive) in the collaborative learning process as they learn fractional concepts in a meaningful way. The findings show that a 3D virtual environment can support collaborative learning in primary school through its ability to enhance students’ engagement (behavioral, affective and cognitive) in the collaborative learning process. 相似文献
13.
Dirk T. Tempelaar Alexandra Niculescu Bart Rienties Wim H. Gijselaers Bas Giesbers 《The Internet and Higher Education》2012,15(3):161-169
This empirical study investigates students' learning choices for mathematics and statistics in a blended learning environment, composed of both online and face-to-face learning components. The students (N = 730) were university freshmen with a strong diversity in prior schooling and a wide range of proficiency in quantitative subjects. In this context, we investigated the impact that individual differences in achievement emotions (enjoyment, anxiety, boredom, hopelessness) had on students' learning choices, in terms of the intensity of using the online learning mode versus the face-to-face mode. Unlike the general level of learning activities, which is only minimally influenced by achievement emotions, these emotions appear to have a moderately strong effect on a student's preference for online learning. Following this, we explored the antecedents of achievement emotions. Through the use of path-modeling, we conclude that while goal setting behavior only marginally impacts achievement emotions, effort views—a crucial component of the social-cognitive model of implicit theories of intelligence—have a substantial impact on achievement emotions. 相似文献
14.
Little research has been conducted to differentiate between multiple, and frequently simultaneously available, discrete object foci in academic achievement situations that emotions can be generated from, including technology and academic topics. Using R. Pekrun’s control-value theory of achievement emotions and Sharples and colleagues’ Mobile Learning Theory, we examined whether appraisals of control over technology and task value predicted emotions directed toward using a mobile app (technology-related emotions) and queer history content (topic emotions). In turn, we examined whether technology-related and topic emotions predicted objective and subjective knowledge outcomes. The main results of this study that examined 57 undergraduate students at a Canadian University were the following: (1) Learners reported high mean levels of technological control over the app. (2) Relatively high mean levels of task value. (3) High mean levels of enjoyment and low mean levels of boredom across both technology-related and topic emotions. (4) Learners’ appraisals of task value contributed to multiple regression models that statistically significantly predicted all emotions; appraisals of control over technology contributed to the multiple regression model (along with task value) that statistically significantly predicted technology-related enjoyment. And (5) technology-related enjoyment and topic boredom contributed to multiple regression models that statistically significantly predicted perceived success of learning. Findings and implications are discussed from a critical-analytical perspective. 相似文献
15.
Chun-Yen Tsai 《International Journal of Science Education》2019,41(9):1139-1158
This study investigates how affective dispositions influencing students’ moral judgments can both shape their response to individual enjoyment from learning ethics (IE-LE) and predict their individual enjoyment from learning socio-scientific issues (IE-LSSI). Tenth-grade participants from southern Taiwan (n?=?770) responded to survey items that support four subscales: science classroom, news media, IE-LE and IE-LSSI. Structural equation modelling analyses of these subscales found them to be empirically separable, structurally reliable and valid for investigating how students’ affective and self-related cognitive responses can predict their self-evaluated state of IE-LE and IE-LSSI. Viewed from the impact contribution of science classroom and news media, learning enjoyment plays a pivotal role in igniting and sustaining students’ personal attention when discussing IE-LE and IE-LSSI in the classroom. The implication of this study is that by encouraging students to think ethically about issues of science and allowing them to investigate SSI-related issues from a variety of news media sources within the classroom context, teachers can provide opportunity for students to explore science issues that may be well connected to their personal enjoyment of ethics and sense of freedom to learn within a science-related classroom environment. 相似文献
16.
在协作学习中学习投入与学习成效紧密相关,是学生进行有效参与和深度学习的必要条件。但目前的研究大多针对个人学习投入,缺乏在协作学习中小组学习投入的相关研究。在前人研究基础上,本研究从认知投入、行为投入、社会投入、情感投入四个维度构建了在线协作学习中小组学习投入的分析模型,并通过实证研究进一步探索小组投入分析模型各维度与小组学习成绩之间的关系。结果表明,在小组学习投入中行为投入、社交投入与小组成绩呈显著正相关关系,而积极、消极、困惑三类情感投入则与小组成绩呈负相关关系。研究同时发现,高分组在中立情感投入、认知投入的问题和元认知维度中的均值都高于低分组。最后,通过分析在线小组学习投入与成绩之间的关系,为今后优化学习支持服务以及提高小组成员协作质量提供了依据。 相似文献
17.
This 2-year longitudinal study examined relations between enjoyment of learning in Chinese and mathematics, two major subjects in Chinese schools, and indexes of school performance. The participants included 1041 students (501 boys) initially in third, fifth, and seventh grades (mean age = 10.49 years) in China. Data on enjoyment of Chinese and mathematics were collected from students' self-reports and data on school performance were collected from multiple sources in 2017 and 2019. The results showed that enjoyment of mathematics positively predicted later academic achievement, self-perceptions of academic competence, teacher-rated school competence, and peer-assessed leadership-social competence. Enjoyment of Chinese negatively predicted later mathematics achievement and self-perceptions of academic competence and nonsignificantly predicted other school performance variables. The results were discussed in Chinese context. 相似文献
18.
Concept maps and Vee diagrams: two metacognitive tools to facilitate meaningful learning 总被引：2，自引：0，他引：2
Joseph D. Novak 《Instructional Science》1990,19(1):29-52
This paper describes two metacognitive tools, concept mapping and Vee diagramming, and reports on research utilizing these tools from grades one through university instruction. The psychological and epistemological foundations underlying these tools is presented briefly. The issues of the dominantly rote-mode nature of much school learning and the resistance of studients (and teachers) to move to meaningful learning strategies fostered by concept mapping and Vee diagramming are discussed. The data available to date from a variety of qualitative and quantitative research studies strongly support the value of these metacognitive tools both for cognitive and affective gains. 相似文献
19.
ChanMin Kim Seung Won Park Joe Cozart 《British journal of educational technology : journal of the Council for Educational Technology》2014,45(1):171-185
We investigated what factors would be related to students' achievement in mathematics courses offered at a virtual high school. This was an attempt to understand why some succeed and some do not as well as to suggest what should be done to help with student success. Seventy‐two students responded to a self‐report survey on motivation (ie, self‐efficacy, intrinsic value), mathematics achievement emotions (ie, anxiety, anger, shame, hopelessness, boredom, enjoyment, pride), and cognitive processes (ie, cognitive strategy use, self‐regulation). A three‐step hierarchical multivariate regression was employed to examine which of the factors predict student achievement. Results showed that motivation accounted for approximately 13% of the variance in student achievement and self‐efficacy was the significant individual predictor of student achievement. However, when achievement emotions were added to the analysis, self‐efficacy failed to predict student achievement and emotions accounted for 37% of the variance in student achievement. Cognitive strategy use and self‐regulation did not explain any additional variance in the final scores. Findings are discussed and implications for future research and development are also suggested. 相似文献