Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: development of a measure and initial test. MIS Quarterly, 19(2), 189–211. Chris is an Intensivist and ECMO specialist at the Alfred ICU in Melbourne. He is also a Clinical Adjunct Associate Professor at Monash University. He is a co-founder of the Australia and New Zealand Clinician Educator Network (ANZCEN) and is the Lead for the ANZCEN Clinician Educator Incubator programme. He is on the Board of Directors for the Intensive Care Foundation and is a First Part Examiner for the College of Intensive Care Medicine. He is an internationally recognised Clinician Educator with a passion for helping clinicians learn and for improving the clinical performance of individuals and collectives. We used partial least squares (PLS), a component-based structural equation modeling technique, for data analysis. Chin and Newsted ( 1999) stated that PLS allows latent constructs to be modeled as formative or reflective indicators and issues minimal restrictions on the measurement scales, sample size, and residual distribution. We used SmartPLS 3.0 as the analytical software (Ringle et al. 2005) to evaluate the research model and then tested the hypotheses. 4.3.1 Psychometric properties Students’ perceived level of online self-regulated learning relatedness is positively associated with their perceived level of enjoyment. 3.4 Perceived usefulness Egger, J. W. (2008). Grundlagen der Psychosomatik – Zur Anwendung des biopsychosozialen Krankheitsmodells in der Praxis. Psychologische Medizin, 19(2), 12–22.

Neben der Stabilisierung intrinsischer Funktionen für die wasm32-Plattform bringt das Release Ergänzungen für Makros mit. Cleary, T., & Zimmerman, B. J. (2004). Self-regulation empowerment program: A schoolbased program to enhance self-regulated and self-motivated cycles of student learning. Psychology in the schools, 41(5), 537–550. Baumann, K., & Linden, M. (2008). Weisheitskompetenzen und Weisheitstherapie. Die Bewältigung von Lebensbelastungen und Anpassungsstörungen. Lengerich: Pabst Science. Pressure-time (top), flow-time (middle) and volume-time (bottom) curves showing the characteristic features of dynamic hyperinflation resulting in high PEEPi (From DerangedPhysiology.com) intrinsischer Wert {m} spec. intrinsic value [of money] Stoffwert {m} [des Geldes] curr. intrinsic zone i-Zone {f} [Intrinsic-Zone] phys. (intrinsic) angular momentum Drall {m} [Drehimpuls] phys. intrinsic angular momentum Eigendrehimpuls {m} phys. intrinsic data type vordefinierter Datentyp {m} comp. intrinsic sympathomimetic activity intrinsische sympathomimetische Aktivität {f} med. intrinsic tooth discolouration [Br.] innere Zahnverfärbung {f} dent. cellular intrinsic fiber cementum [Am.] zellulärer Eigenfaserzement {m} dent. intrinsic blood coagulation system intrinsisches Blutgerinnungssystem {n} biochem. med. intrinsic theory of value intrinsische Bewertungsmethode {f} econ. intrinsic value of gold Eigenwert {m} des Goldes fin.

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Taylor, S., & Todd, P. (1995). Assessing IT usage: the role of prior experience. MIS Quarterly, 19(4), 561–570. Hsu, H. C. K., Wang, C. V., & Levesque-Bristol, C. (2019). Reexamining the impact of self-determination theory on learning outcomes in the online learning environment. Education and information technologies, 24(3), 2159–2174. Brähler, E. & Scheer, J. W.(1979). Scaling of psychomatic by means of the Giessen inventory (GBB). Psychotherapie und medizinische Psychologie, 29(1), 14–27. Students’ perceived level of autonomy when they utilize online learning is positively associated with their perceived level of usefulness. H2

The goal of the present study is based on SDT to explain the role of intrinsic and extrinsic motivation in continued intention to engage in online SRL. The direct relation from intrinsic and extrinsic motivation to continued intention, from perceived autonomy, competence and relatedness to intrinsic motivation and extrinsic motivation, are examined. To achieve the study objective, a theory model is empirically tested by 227 undergraduates who enrolled in online learning. Wang, T. H. (2011). Developing Web-based assessment strategies for facilitating junior high school students to perform self-regulated learning in an e‑Learning environment. Computers & Education, 57(2), 1801–1812. https://doi.org/10.1016/j.compedu.2011.01.003. Taylor, G., Jungert, T., Mageau, G. A., Schattke, K., Dedic, H., & Rosenfield, S. (2014). A self-determination theory approach to predicting school achievement over time: the unique role of intrinsic motivation. Contemporary Educational Psychology, 39(4), 342–358. https://doi.org/10.1016/j.cedpsych.2014.08.002. Students’ perceived level of autonomy when they utilize online learning is positively associated with their perceived level of enjoyment. 3.2 Perceived competence Dahmen, B. (1993). Verhaltenstherapie. In A. Schorr (Hrsg.), Handwörterbuch der angewandten Psychologie. Berlin: Deutscher Psychologen Verlag.

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Benight, C. C., & Bandura, A. (2004). Social cognitive theory of posttraumatic recovery: the role of perceived self-efficacy. Behaviour research and therapy, 42(10), 1129–1148.

Bøe, T., Gulbrandsen, B., & Sørebø, Ø. (2015). How to stimulate the continued use of ICT in higher education: Integrating Information Systems Continuance Theory and agency theory. Computers in Human Behavior, 50(9), 375–384. Perceived usefulness (H7) and perceived enjoyment (H8) are significant associated with the continued intention to engage in online SRL, and perceived enjoyment is more related to continued intention than did perceived usefulness. It is interesting that in the SRL context, students’ willingness for online learning depends more on intrinsic motivation. This outcome confirms that intrinsic motivation is superior in self-regulated situations. Chen, K. C., & Jang, S. J. (2010). Motivation in online learning: testing a model of self-determination theory. Computers in Human Behavior, 26(4), 741–752. Garcia, T., & Pintrich, P. R. (1994). Regulating motivation and cognition in the classroom: The role self-schemas and self-regulatory strategies. In D. H. Schunk & B. J. Zimmerman (Eds.), Self-regulation of learning and performance: issues and educational applications (pp. 127–153). Hillsdale: Lawrence Erlbaum. Ryan, R. M., & Deci, E. L. (2020). Intrinsic and extrinsic motivation from a self-determination theory perspective: definitions, theory, practices, and future directions. Contemporary Educational Psychology, https://doi.org/10.1016/j.cedpsych.2019.101831.

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This study verified the structural hypotheses of the proposed model by analyzing the structural estimates produced by PLS. A standard bootstrapping procedure (Yung and Bentler 1996) with 1000 re-samples comprising identical number of cases in the original sample was applied to determine the significance of each estimated path coefficient. Fig. 2 shows the results of the structural path analysis. Standardized regression coefficients are shown above each path, and the R‑squared is shown with each endogenous variable. Bardone-Cone, A. M., Abramson, L. Y., Vohs, K. D., Heaterton, T. F., & Joiner T. E. Jr. (2006).Predicting bulimic symptoms: An interactive model of self-efficacy, perfectionism, and perceived weight status. Behavior and research therapy, 44(1), 27–42. Joo, Y. J., Park, S., & Shin, E. K. (2017). Students’ expectation, satisfaction, and continuance intention to use digital textbooks. Computers in Human Behavior, 69(4), 83–90. Deci, E. L., & Ryan, R. M. (2008). Self-determination theory: a macrotheory of human motivation, development, and health. Canadian Psychology, 49(3), 182–185.

Bowsher, J. E., & Keep, D. (1995). Toward and Understanding of Three Control Constructs: Personal Control, Self-Efficacy, and Hardiness. Issues in Mental Health Nursing, 16, 33–50.

The present study explores the role of perceived autonomy, perceived competence and perceived relatedness in explaining the influence of intrinsic and extrinsic motivation on the continued intention to engage in online SRL. Intrinsic and extrinsic motivations are operationalized using the constructs of perceived enjoyment and perceived usefulness, respectively. Interestingly, among the three basic psychological needs, perceived competence of online SRL seems to be the most important influence on intrinsic motivation (H3) and extrinsic motivation (H4). This difference is somewhat surprising because SDT asserts that autonomy is essential to users’ intrinsic and extrinsic motivation (Roca and Gagné 2008). This finding confirms that competence has a stronger relationship with motivation for online SRL. First, high self-regulation for learning is known as the nature of SRL, and therefore, autonomy may be taken for granted. Second, competence may be a scarce resource in the academic context and probably becomes more important for the development of intrinsic and extrinsic motivation (Sørebø et al. 2009). Ong, C. S., & Lai, J. Y. (2006). Gender differences in perceptions and relationships among dominants of e‑learning acceptance. Computers in Human Behavior, 22(5), 816–829. Online learning refers to one type of educational instruction with various online technologies, either completely asynchronous or partly synchronous learning, and with no appointed face-to-face time and location (Broadbent 2017). Self-regulating means controlling a process or activity by the individual who is involved in it, and this control includes a series of individual’s cognitive activities and behaviors, i.e., observing, mastering and regulating (Garcia and Pintrich 1994). In autonomous online environments, it is up to students to decide when, where and how to learn; thus, students are responsible for their own learning (Wang et al. 2013), and self-regulation of learning becomes more important in an online context than in a traditional context (King et al. 2000; Wijekumar et al. 2006).