Drivers of technology adoption during the COVID-19 pandemic: The motivational role of psychological needs and emotions for pre-service teachers
The vital role of motivation becomes even more evident when considering the digital transformation of learning and teaching environments, especially with the effect of the pandemic. Basic psychological needs and emotions, which have not been comprehensively examined together despite their important...
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Veröffentlicht in: | Social psychology of education 2022-06, Vol.25 (2-3), p.567-592 |
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description | The vital role of motivation becomes even more evident when considering the digital transformation of learning and teaching environments, especially with the effect of the pandemic. Basic psychological needs and emotions, which have not been comprehensively examined together despite their important roles in motivating, draw attention. Accordingly, this study aims to reveal the psychological, emotional, and individual variables that influence the pre-service teachers’ intention to use technology, and to evaluate and validate the predictive power of a proposed model. The technology acceptance model formed the basis of the proposed model, and the model was extended with the self-determination theory (competence, autonomy, relatedness) and a framework of emotions (enjoyment, playfulness, anxiety, frustration). Data were collected online from 591 pre-service teachers studying in 10 different departments of a state university. In data analysis PLS-SEM, PLSpredict and multi-group analysis were performed. The results revealed that the model explains 79.8% of the intention and that the predictive power of the model is high. The relationship between competence and perceived ease of use represents the strongest relationship in the model, and the most influential construct on intention is enjoyment. These findings suggest that both intrinsic and extrinsic motivation play a major role in technology acceptance, especially during the pandemic. In addition, innovativeness, which is related to technology use and motivation, had various moderator effects on the relationships. Findings indicate that the model, which offers a motivational approach based on basic psychological needs and emotions, provides rare information and has high relevance for the field. |
doi_str_mv | 10.1007/s11218-022-09702-w |
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Basic psychological needs and emotions, which have not been comprehensively examined together despite their important roles in motivating, draw attention. Accordingly, this study aims to reveal the psychological, emotional, and individual variables that influence the pre-service teachers’ intention to use technology, and to evaluate and validate the predictive power of a proposed model. The technology acceptance model formed the basis of the proposed model, and the model was extended with the self-determination theory (competence, autonomy, relatedness) and a framework of emotions (enjoyment, playfulness, anxiety, frustration). Data were collected online from 591 pre-service teachers studying in 10 different departments of a state university. In data analysis PLS-SEM, PLSpredict and multi-group analysis were performed. The results revealed that the model explains 79.8% of the intention and that the predictive power of the model is high. The relationship between competence and perceived ease of use represents the strongest relationship in the model, and the most influential construct on intention is enjoyment. These findings suggest that both intrinsic and extrinsic motivation play a major role in technology acceptance, especially during the pandemic. In addition, innovativeness, which is related to technology use and motivation, had various moderator effects on the relationships. 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Basic psychological needs and emotions, which have not been comprehensively examined together despite their important roles in motivating, draw attention. Accordingly, this study aims to reveal the psychological, emotional, and individual variables that influence the pre-service teachers’ intention to use technology, and to evaluate and validate the predictive power of a proposed model. The technology acceptance model formed the basis of the proposed model, and the model was extended with the self-determination theory (competence, autonomy, relatedness) and a framework of emotions (enjoyment, playfulness, anxiety, frustration). Data were collected online from 591 pre-service teachers studying in 10 different departments of a state university. In data analysis PLS-SEM, PLSpredict and multi-group analysis were performed. The results revealed that the model explains 79.8% of the intention and that the predictive power of the model is high. The relationship between competence and perceived ease of use represents the strongest relationship in the model, and the most influential construct on intention is enjoyment. These findings suggest that both intrinsic and extrinsic motivation play a major role in technology acceptance, especially during the pandemic. In addition, innovativeness, which is related to technology use and motivation, had various moderator effects on the relationships. Findings indicate that the model, which offers a motivational approach based on basic psychological needs and emotions, provides rare information and has high relevance for the field.</description><subject>Analysis</subject><subject>Automobile drivers</subject><subject>Classroom Environment</subject><subject>Competence</subject><subject>COVID-19</subject><subject>Data Analysis</subject><subject>Education</subject><subject>Educational psychology</subject><subject>Educational Technology</subject><subject>Emotional Response</subject><subject>Emotions</subject><subject>Epidemics</subject><subject>Incentives</subject><subject>Intention</subject><subject>Motivation</subject><subject>Pandemics</subject><subject>Personality and Social Psychology</subject><subject>Prediction</subject><subject>Preservice Teacher Education</subject><subject>Preservice Teachers</subject><subject>Psychological Needs</subject><subject>Psychological Patterns</subject><subject>Self Determination</subject><subject>Sociology of Education</subject><subject>Teacher education</subject><subject>Teachers</subject><subject>Technology Acceptance Model</subject><subject>Technology adoption</subject><subject>Technology Uses in Education</subject><subject>Usability</subject><issn>1381-2890</issn><issn>1573-1928</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9Uk1v1DAQjRCIlsIfQAJZ4sIlxR_5sDlUqrYFiir1UrhaXmey6yprBzvZan8Ff5lJU7YUIeSDrZn33nhmXpa9ZvSYUVp_SIxxJnPKeU5VTXl--yQ7ZGUtcqa4fIpvIVnOpaIH2YuUbiidaPx5diBKhPOaHmY_z6LbQkwktGQAu_ahC6sdMU3oBxc8acbo_IoMayCLq-8XZyhNeuMb2Dj7kVxjeBMGtzUT2HQkhg4mqT7t7HqSchajHqBJBFkEJnTwibQhkj5CniBunQWsbewa__Eye9aaLsGr-_so-_bp_HrxJb-8-nyxOL3MbaHEkEte1cCakoO0ZsmpWpaNpYYtKyNLRgVQoRQOQVpM1rJSyhbGGlPSouYUKnGUncy6_bjcQGPBD9F0uo9uY-JOB-P044x3a70KW62YFHXFUeD9vUAMP0ZIg964ZKHrjIcwJo0frBQvKykR-u4v6E0YI45rQklOcU28ekCtTAfa-TZgXTuJ6tOaYguiKqayx_9A4bnbSPDQOow_IvCZYGNIKUK775FRPflBzzbSaAh9ZyN9i6S3f05nT_ntGwS8mQEQnd2nz78yUVDcBubFnE_95B-IDy3_p-wv6yDdKA</recordid><startdate>20220601</startdate><enddate>20220601</enddate><creator>Sahin, Ferhan</creator><creator>Sahin, Yusuf Levent</creator><general>Springer Netherlands</general><general>Springer</general><general>Springer Nature B.V</general><scope>7SW</scope><scope>BJH</scope><scope>BNH</scope><scope>BNI</scope><scope>BNJ</scope><scope>BNO</scope><scope>ERI</scope><scope>PET</scope><scope>REK</scope><scope>WWN</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>3V.</scope><scope>7XB</scope><scope>88B</scope><scope>88G</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>CJNVE</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>M0P</scope><scope>M2M</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PQEDU</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20220601</creationdate><title>Drivers of technology adoption during the COVID-19 pandemic: The motivational role of psychological needs and emotions for pre-service teachers</title><author>Sahin, Ferhan ; 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Basic psychological needs and emotions, which have not been comprehensively examined together despite their important roles in motivating, draw attention. Accordingly, this study aims to reveal the psychological, emotional, and individual variables that influence the pre-service teachers’ intention to use technology, and to evaluate and validate the predictive power of a proposed model. The technology acceptance model formed the basis of the proposed model, and the model was extended with the self-determination theory (competence, autonomy, relatedness) and a framework of emotions (enjoyment, playfulness, anxiety, frustration). Data were collected online from 591 pre-service teachers studying in 10 different departments of a state university. In data analysis PLS-SEM, PLSpredict and multi-group analysis were performed. The results revealed that the model explains 79.8% of the intention and that the predictive power of the model is high. 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subjects | Analysis Automobile drivers Classroom Environment Competence COVID-19 Data Analysis Education Educational psychology Educational Technology Emotional Response Emotions Epidemics Incentives Intention Motivation Pandemics Personality and Social Psychology Prediction Preservice Teacher Education Preservice Teachers Psychological Needs Psychological Patterns Self Determination Sociology of Education Teacher education Teachers Technology Acceptance Model Technology adoption Technology Uses in Education Usability |
title | Drivers of technology adoption during the COVID-19 pandemic: The motivational role of psychological needs and emotions for pre-service teachers |
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