• Human Ecology Research
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• v.55 no.5
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• pp.527-538
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• 2017

This study examines the effects of university students' types of self-determination and academic emotions on their learning community participant competence. The subjects were 234 early-childhood preservice teachers attending a university or college in the Kyonggi and Incheon area of Korea. The first metric created by Bak et al. (2005) measured early-childhood preservice teachers' types of self-determination. The second metric developed by Kim & Kim (2016) measured their levels of learning community participant competence. The thirds metric, originally developed by Kim (2012) and So (2010), was modified by Chung (2015) to measure the academic emotions of subjects. The test results were analyzed by correlation and multi-regression techniques using SPSS 21 for Windows. The findings were as follows. First, there were significant relationships between the subjects' types of self-determination and the levels of learning community participant competence. Second, there were significant relationships between the subjects' academic positive and negative emotions and the levels of learning community participant competence. Third, the subjects' levels of learning community participant competence were perceived differently according to their academic emotions. Based on these results, implications pertaining to academic emotions on learning community participant competence are suggested.

• Journal of Korean Academy of Nursing
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• v.49 no.4
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• pp.495-504
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• 2019

Purpose: Nursing students experience a high degree of perceived stress during skills training. The resulting academic sentiment is worthy of research. This study examined the learning motivation as a mediator in the association between perceived stress and positive deactivating academic emotions in nursing students undergoing skills training. Methods: A survey was conducted on 386 third-year undergraduate nursing students at a university in Changchun, China, in 2017. The survey included the items on perceived stress, learning motivation during nursing skill training, and general academic emotion. There were 381 valid responses (response rate=98.7%). Based on the results of partial correlation and stepwise multiple regression equations, the study examined the mediation model between perceived stress, learning motivation and positive-deactivating academic emotions using process 2.16 (a plug-in specifically used to test mediation or moderation effect in SPSS). Results: There was a significant negative correlation between students' perceived stress and learning motivation during nursing skills training and positive-deactivating academic emotions. Nervousness, loss of control, and interest in developing reputation had significant predictive effects on positive-deactivating academic emotions. The mediating model was well supported. Conclusion: Learning motivation during nursing skills training lessened the damage of perceived stress on positive-deactivating academic emotions. Improving students' motivation to learn could reduce their perceived stress and build more positive emotions. Positive emotions during learning played an important role in helping nursing students improve skills and enhance their nursing competence.

• Educational Technology International
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• v.17 no.2
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• pp.151-174
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• 2016

This study examined the effects of simulation game-based learning on academic emotions (positive, negative) and achievement (factual, conceptual, procedural knowledge acquisition). Sixty-three students from a high school located in South Korea were chosen for the study. The students were assigned to either an experimental group for simulation game-based learning or a comparison group for instructor-led lectures. The results demonstrated that there was a significant difference between the comparison and experimental groups in both positive and negative academic emotions. However, there was no significant difference in factual, conceptual and procedural knowledge acquisition. The results indicate that simulation game-based learning generates more positive emotions than instructor-led lectures.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.2
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• pp.582-595
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• 2016

Effects of learning variables on academic achievement were major goal of this study. The differences of learning emotions, attitudes, flow and major satisfaction by grades of college students in medical school were proposed to conduct. Participants of this study consisted of 194 students of 1st and 2nd grade plus 121 students of 3rd and 4th grade in medical school. They completed the survey questionnaires composed of learning emotions, attitudes, flow and major satisfaction. Collected data were analyzed by t-test and stepwise multiple regression. Two kinds of results achieved as follows: First, there were differences of negative and positive emotions, and learning attitudes but were found no differences of learning flow and major satisfaction by grades. Second, there were significant effects of learning emotions and attitudes on academic achievement and also found differences of variables that affect academic achievement by grades. Based on these results, we think necessitate of considering learning emotions and behaviors in developing training programs and students support systems for medical school are obliged.

• Journal of Industrial Convergence
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• v.21 no.11
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• pp.75-83
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• 2023

This study aimed to identify the effect of academic emotions, learning flow and perceived teaching presence for academic achievement of nursing students in an uncontacted online class learning in the convergence society. The participants were 127 nursing students; data were analyzed using t-test, ANOVA, pearson correlation, multiple regression. It was found that: nursing students showed higher score at academic emotions, higher learning flow, and higher perceived teaching presence, higher score for academic achievement. The main factors influencing academic achievement were academic emotions, learning flow and perceived teaching presence. They explained about 42.7% of the academic achievement. Therefore, when operating uncontacted online classes for nursing students, it is necessary to consider the factors of learners, the personal efforts of the instructor, and systematic support for strengthening the instructor's capabilities.

• The Journal of Korean Association of Computer Education
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• v.15 no.4
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• pp.61-77
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• 2012

The purpose of this study was to examine the structural relationship among task value, self-efficacy, classroom goal structure, and academic emotions(enjoyment, fear, boredom) for promoting self-regulated learning in e-learning course. The results showed that task value, self-efficacy, class goal structure influenced academic emotions and self-regulated learning, and enjoyment had mediation effects among exogenous variables and self-regulated learning. The findings offer implications of facilitating self-regulated learning while considering academic emotions.

• Journal of Integrative Natural Science
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• v.9 no.2
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• pp.144-151
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• 2016

The purpose of this study is to investigate the emotion effects on academic achievement for university students. The results are as follows. Resulting on the each emotions difference by the statistical variables, anxiety scores by gender showed a significant difference in the p<.01 level(F=7.685). The males anxiety(2.478, standard deviation: 0.180) had significantly lower scores than females(3.076, standard deviation: 0.168). But fear, anger, activity, and sociability scores were not significantly different respectively between male and female students. To see the emotions effect of academic achievement, the analysis method of the linear regression line was used. As the result, anxiety, fear, anger, activity, and sociability did not significantly influence academic achievement. And so unlike previous methods, the analysis method of the quadratic regression curve was used. As the result, anxiety, fear, anger, activity, and sociability showed did significantly influence academic achievement respectively within 5% of statistical significance level, to more than F=3.06. Therefore, the values on academic achievement of the each anxiety, fear, anger, activity, and sociability showed a quadratic regression curve. That is, [Academic achievement]=$-0.9685{\times}[Anxiety]^2+5.1342{\times}[Anxiety]+8.2679$,[Academic achievement]=$-1.0638{\times}[Fear]^2+5.5694{\times}[Fear]+7.5635$,[Academic achievement]=$-1.3497{\times}[Anger]^2+9.1284{\times}[Anger]+0.6720$,[Academic achievement]=$-1.0589{\times}[Activity]^2+7.4386{\times}[Activity]+1.8272$,[Academic achievement]=$-1.6830{\times}[Sociability]^2+11.2325{\times}[Sociability]-3.8258$. Therefore, we were able to determine the following conclusions. First, we were able to predict the degree of academic achievement by the each emotions scale. Second, when the each emotion scores of students was a moderate, the academic achievement was most excellent. So, in order for the students to become higher academic achievement, the maintenance of medium degree of the each emotions scores is required.

• Journal of Industrial Convergence
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• v.20 no.11
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• pp.41-47
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• 2022

This study explored the academic emotions of university freshmen depending on the type of online class(pre-recorded lecture vs. real time online class) that they took during the COVID-19 lockdown. 170 freshmen participated in the survey based on the 'Academic Emotion Questionnaire(AEQ)', and the statistical results are as follows; Firstly, research showed that the participants felt higher positive emotions for pre-recorded lecture than for real time online class, and higher negative emotions for real time online class than for pre-recorded lecture(p < .01). Secondly, participants felt different emotions depending on English level(p < .01). Thirdly, participants felt different emotions depending on their majors(p < .01). Students majoring in science & engineering felt higher positive emotions than those in humanities & social studies in pre-recorded lecture class. Fourthly, participants felt different emotions depending on gender(p < .01). Female students felt higher negative emotions than male students. Finally, the pedagogical implications and suggestions were discussed.

• Journal of The Korean Association For Science Education
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• v.33 no.2
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• pp.444-465
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• 2013

The purpose of this study is to extract core situations that can arouse various academic emotions and to analyze the characteristics of intensity-frequency of these academic emotions from Korean elementary students in Science classes. To accomplish this study, authors conducted a survey of 642 sixth grade students. The result of the study are as follows: First, science academic emotions varied depending on each of the science learning situations. On the whole, positive-emotions were aroused in science experiment situations and negative-emotions were aroused in evaluation, personality of individuals and other people, teaching-learning method and science experiment situations. If teachers want to manage a specific emotion, they should control the core situations that can arouse that specific emotion. Second, positive-emotions appeared more than negative-emotions in intensity and frequency. But boredom, annoyance and stuffiness appeared the most among negative-emotions. Teachers have to reduce students' boredom, annoyance and stuffiness that are aroused in their science classes. Based on the results, authors become assured that introduction of the emotions was a very useful method in enhancing Korean elementary students' affective domain achievement in science classes.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.8-17
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• 2019

The main purpose of this study isto explore the potential of affective computing (AC) platforms in education through two phases ofresearch: Phase I - platform analysis and Phase II - classification of academic emotions. In Phase I, the results indicate that the existing affective analysis platforms can be largely classified into four types according to the emotion detecting methods: (a) facial expression-based platforms, (b) biometric-based platforms, (c) text/verbal tone-based platforms, and (c) mixed methods platforms. In Phase II, we conducted an in-depth analysis of the emotional experience that a learner encounters in online video-based learning in order to establish the basis for a new classification system of online learner's emotions. Overall, positive emotions were shown more frequently and longer than negative emotions. We categorized positive emotions into three groups based on the facial expression data: (a) confidence; (b) excitement, enjoyment, and pleasure; and (c) aspiration, enthusiasm, and expectation. The same method was used to categorize negative emotions into four groups: (a) fear and anxiety, (b) embarrassment and shame, (c) frustration and alienation, and (d) boredom. Drawn from the results, we proposed a new classification scheme that can be used to measure and analyze how learners in online learning environments experience various positive and negative emotions with the indicators of facial expressions.