Perceived Restorativeness in Improving Motivation: History
View Latest Version
Please note this is an old version of this entry, which may differ significantly from the current revision.
Contributor:
Diego Bellini
,
Barbara Barbieri
,
Massimiliano Barattucci
,
Maria Lidia Mascia
,
Tiziana Ramaci

Motivation is an essential element of learning and a determinant of academic success. Notably, high levels of student motivation lead to higher levels of productivity. Therefore, university students need to improve their motivation levels to increase academic achievement. They can improve motivation through job resources such as Perceived Restorativeness.

  • motivation
  • restorative environments
  • stress
  • higher education

1. The Perceived Restorative Quality of the Environment in the Academic Context within the JD-R model.

In the learning environment, a variety of resources or demands may have an influence on individuals. For instance, the perceived quality of the physical environment may determine satisfaction [1][2] and learning efficiency [3][4][5].
Precisely, many aspects of physical design, such as spatial layout or noise, can hinder or improve performance by affecting a student’s physical and psychological resources [5]. More precisely, the environment can allow individuals to relax and distance themselves from everyday thoughts and demands. In this regard, university students have multiple demands placed on them, such as taking exams and engaging in many activities. As a result, they may experience mental fatigue [6][7][8] that, in turn, may reduce their effort level, affect their concentration, and lead to lower academic performance [9]. In this regard, the concept of restorativeness [10] refers to the capacity of the environment “to offer a concrete and available means of reducing suffering and enhancing effectiveness” [11].
Research has paid relatively little attention to the characteristics of learning environments that help students complete restoration to improve their performance.
According to attention restoration theory (ART) [6][12], direct attention is voluntary; it plays a crucial role in controlling distraction, requires effort, and is related to attentional fatigue [11]. The theory describes how the socio-physical environment can support psychological restoration and explains how mental fatigue and direct attention can be restored through four proprieties: Fascination, being away, extent, and compatibility [13].
Fascination is described as an effortless form of attention that allows a fatigued attentional system to rest [11]. This property is present when individuals find a place or situation interesting for them. Being away refers to distancing oneself from routine activities and demands that lead to attentional fatigue. In this condition, students have a sense of being in a different place and/or engaged in different cognitive content [11].
Extent refers to the scope and coherence of the environment that has vast content to the extent that it is possible to get lost in it. Hence, the environment is perceived as a “whole other world” [6]. Finally, compatibility refers to the fit between the demands of the setting and environment and an individual’s goals; the setting and environment should support the actions needed by individuals to achieve their purposes [14].
ART has generally been applied to explain psychological restoration and as a strategy to cope with stress using the natural environment and the learning environment with natural elements [15][16], but recently, some researchers have also examined the role of restoration in the workplace [17][18][19] and in the academic context [20]. In academic environments, Yusli and colleagues [20] found a positive relationship between restorativeness and well-being in a sample of university students.
ART constructs explain how the restorative experience may help students restore or gain internal resources to meet environmental and learning demands.
Therefore, it is important to verify whether the characteristics of the learning environment in reducing stress can be helpful in improving further resources such as, in this research, motivation and flow in the academic context. The relationship between resources and demands and the process that fosters positive outcomes can be described by the JD-R model as follows.

2. The Job Demands–Resources Model (JD-R)

The job demands–resources model (JD-R) [21] is a conceptual framework used to explain the dynamics of resource depletion and restoration on job or study characteristics. Therefore, this model is relevant in understanding the role of restorativeness in the learning environment.
According to the JD-R model, every job (including student activities) is characterized by job demands and job resources [22][23]. Demerouti and colleagues [22] defined job demands as “all physical, psychological or social aspects of the job that require sustained physical or mental effort and that are therefore associated with psychological costs, such as emotional exhaustion” [24], (p. 501). Examples of job demands (in the learning context) are time pressure, long studying hours, noise, and all elements that drain energy. In university or learning contexts, the number of courses or the number of study hours can contribute to mental demands. In contrast, job resources are defined as “those aspects of the job that are functional in achieving work goals in stimulating personal growth and development, and reducing job demands and the associated psychological costs” [24], (p. 501).
Examples of job resources (in the learning context) include support from teachers, colleagues, and the environment (which helps to achieve an individual’s goals) and performance feedback, which may enhance learning. Job demands and job resources can be both external (e.g., rewards, task variety, and social support) and internal (cognitive) [22]. In the learning context, the JD-R model premises that the combination of high job demands and high job resources results in learning engagement [25].
The JD-R model also incorporates personal resources [26], referring to all aspects of the self that are generally linked to resilience and reflect an enhanced self-perceived ability to successfully influence one’s environment [23][27].
Personal resources positively affect job resources [28] and strengthen the positive relationship between job resources and well-being [28]. Specifically, personal resources are relevant antecedents of motivation and can promote job/academic resources, which, in turn, can further increase personal resources [29].
Restorative environments, or restorativeness, can be considered job resources because of their ability to replenish psychological resources and help students to gain some psychological distance from ordinary activities and engage effortless attention in some interesting activities.
Essentially, the JD-R model combines two psychological processes, a stressful process and a motivational process, which can explain the dynamics of resource depletion and restoration.
A stressful process, due to excessive job demands and lack of resources, may lead to negative outcomes such as poor performance [28][30]. Excessive job demands drain energy and other resources [21]. This stress process is also aligned with the Conservation of Resources (COR) theory [31], which suggests that stress occurs when an individual’s energy resources are depleted or new resources are not available.
A motivational process that is promoted by abundant job resources may lead to positive outcomes such as superior performance [32]. Job resources enhance employee energy and motivation. More precisely, the availability of resources can counteract the negative effects of demands [21][33][34], foster worker growth, learning, and development [35][36], and decrease work stress and burnout in the learning context [37].
Increasing resources protects workers against the adverse effects of job demands and promotes work engagement, whereas a lack of resources could have health-impairing consequences [38]. A recent meta-analysis [39] summarized the positive effect of job resources on work engagement and satisfaction. Generally, resources can positively affect individuals, facilitate their engagement, protect them from psychological discomfort [40], and predict motivation [21].

3. Restorativeness and Motivation

Based on the JD-R model, which assumes job resources (i.e., restorativeness) enhance employee energy and motivation fostering worker growth, learning, and development [35][36], through a motivational process, the researchers expect that restorativeness is positively linked with student motivation. Motivation in the JD-R model is a mediator of the relationship between job resources (in this research, restorativeness in the learning environment) and positive outcomes (e.g., flow in this case). Generally, the positive effects of the environment have been demonstrated in previous studies [19][41][42][43], but the relationship with restorativeness, motivation, and flow has yet to be considered.
In the following, the researchers address the relationships between learning environments and two relevant psychosocial dimensions related to learning (i.e., flow and motivation).

4. Flow

Csikszentmihalyi described the state of flow as ‘‘a sense that one’s skills are adequate to cope with the challenges at hand, a goal-directed, rule-bound action system that provides clear clues as to how well one is performing…concentration is intense…and the sense of time becomes distorted’’ [44]. Therefore, when individuals enter a flow state, distractions are reduced. Flow occurs when an individual’s skills are sufficient to meet the challenges [44] and whenever their skills fit the situational demands [45]. Individuals perceive a challenge–skills balance, and they believe the task is achievable. If the challenge level or demands exceed an individual’s skill or resources for a task, the situation can produce stress, and the individual may disengage. The European Flow-Researchers’ Network [46] defined flow as “a gratifying state of deep involvement and absorption that individuals report when facing a challenging activity and they perceive adequate abilities to cope with it”.
Three conditions are needed to be in a flow state: Clear goals throughout the activity or process, immediate feedback, and a balance between challenges and skills [47].
Flow is positively related to focused attention, losing track of time, being in control, becoming less self-conscious, enjoying what one is doing, and performance [48]. Specifically, in relation to learning aims, flow was found to be positively related to exam performance [49], goal progress [50], and academic success [51][52][53]. It is a form of psychological well-being that is desirable in academic learning contexts [54]. Bakker [55] applied the flow experience to the working condition, comparing the flow state with work engagement. Specifically, he defined flow as a short-term peak experience characterized by absorption (immersion and total concentration in the work), work enjoyment (pleasure experienced by people during work), and intrinsic work motivation (working to feel pleasure and satisfaction).

5. Restorativeness and Flow

Because the experience of flow, as the researchers have noted, is a balance between skills (or resources) and challenges (or demands), it can be examined according to the JD-R model. Specifically, students can experience a state of flow in the learning context [56] when they can access job resources such as environmental resources in the learning place or when job demands are balanced with high resources (in this case, environmental resources and motivation).
Some authors have found that job resources are an antecedent of flow [57][58] and well-being [55][58].
Specifically, the restorativeness quality of the learning environment, which is functional in achieving work goals and encourages personal growth, development, and learning [35], acts as a job resource, restores direct attention, and promotes concentration through ART.
A recent meta-analysis [59] confirmed that flow had a positive association with many motivational indicators, such as volition, engagement, goal orientation, achievement motive, interest, and intrinsic motivation, and with emotional aspects and performance (because individuals are highly concentrated). Thus, the researchers also expect a positive effect of motivation on flow.

6. Motivation and Flow

Motivation refers to acting to do or obtain something and may significantly affect higher academic performance [60]. Motivation is an important part of human behavior that influences student energy, persistence in tasks [61], and academic achievement [62][63]. There are two types of motivation, intrinsic and extrinsic [64]. Intrinsic motivation refers to activities carried out for one’s own interest and enjoyment [65]. It refers to activities that provide an individual with personal satisfaction and are not dependent on external rewards [66].
Intrinsic motivation is associated with higher performance, school achievement [67], engagement [68][69][70], and learning and development [71]. Csikszentmihalyi [44] suggests that intrinsic motivation has a relevant role in experiencing a state of flow (which originates from motivation theory) because it serves to energize, direct, and sustain behaviors [72]. Various studies have shown that intrinsic motivation is positively associated with flow, and motivation facilitates flow states [45][73][74]. Therefore, a higher level of individual motivation can, in turn, become an intrinsically enjoyable mental state [75][76] characterized by absorption and intrinsic work motivation defined by Csikszentmihalyi [44][77] as flow.
Conversely, extrinsic motivation depends on external factors. For example, individuals are motivated by rewards, including in the form of social approval or appreciation. Nevertheless, even when an individual is not intrinsically motivated, extrinsic motivation can positively affect well-being, performance, and outcomes when it is generated by values with which the person identifies [64]. Generally, motivated individuals are more likely to experience flow [73][78]. In addition, motivated students are more likely to engage in a learning context and experience more flow than less motivated students [79]. In their empirical research, Csikszentmihalyi and Nakamura [80] observed that when people show an interest in the activity, they can be absorbed with high levels of engagement and concentration.
Recently, Kong and Wang [81] found a positive relationship between the perception and support of parents and students’ flow experience through the mediating role of student learning motivation.
Therefore, motivation is a relevant resource to promote positive outcomes such as flow. It is relevant to note that resources and flow mutually influence each other: resources can predict flow and flow leads to a greater perception of job resources in a virtuous circle [57].
By contrast, a lack of resources has a detrimental effect on worker motivation and performance because it impedes the achievement of goals and the possibility of learning [82], as reported in the JD-R model.

This entry is adapted from the peer-reviewed paper 10.3390/ijerph192215263

References

  1. Bjork, J.; Albin, M.; Grahn, P.; Jacobsson, H.; Ardö, J.; Wadbro, J.; Ostergren, P.-O.; Skarback, E. Recreational values of the natural environment in relation to neighbourhood satisfaction, physical activity, obesity and wellbeing. J. Epidemiol. Community Health (1978) 2008, 62, e2.
  2. Hill, M.; Epps, K. The Impact of Physical Classroom Environment on Student Satisfaction and Student Evaluation of Teaching in the University Environment. Academy Educ. Leadersh. J. 2010, 14, 65–79.
  3. Choi, S.; Guerin, D.A.; Kim, H.Y.; Brigham, J.K.; Bauer, T. Indoor Environmental Quality of Classrooms and Student Outcomes: A Path Analysis Approach. J. Learn. Spaces 2014, 2. Available online: http://www.libjournal.uncg.edu/ojs/index.php (accessed on 20 October 2022).
  4. Choi, H.-H.; van Merriënboer, J.J.G.; Paas, F. Effects of the Physical Environment on Cognitive Load and Learning: Towards a New Model of Cognitive Load. Educ. Psychol. Rev. 2014, 26, 225–244.
  5. Xiong, L.; Huang, X.; Li, J.; Mao, P.; Wang, X.; Wang, R.; Tang, M. Impact of Indoor Physical Environment on Learning Efficiency in Different Types of Tasks: A 3 × 4 × 3 Full Factorial Design Analysis. Int. J. Environ. Res. Public Health 2018, 15, 1256.
  6. Kaplan, S. The restorative benefits of nature: Toward an integrative framework. J. Environ. Psychol. 1995, 15, 169–182.
  7. Mosleh, S.M.; Shudifat, R.M.; Dalky, H.F.; Almalik, M.M.; Alnajar, M.K. Mental health, learning behaviour and perceived fatigue among university students during the COVID-19 outbreak: A cross-sectional multicentric study in the UAE. BMC Psychol. 2022, 10, 47.
  8. Smith, A.P. Cognitive Fatigue and the Wellbeing and Academic Attainment of University Students. J. Educ. Soc. Behav. Sci. 2018, 24, 1–12.
  9. Hodson, C.B.; Sander, H.A. Title: Green Urban Landscapes and School-Level Academic Performance. 2016. Available online: http://www.elsevier.com/open-access/userlicense/1.0/1 (accessed on 19 October 2022).
  10. Hartig, T.; Korpela, K.; Evans, G.W.; Gärling, T. A measure of restorative quality in environments. Scand. Hous. Plan. Res. 1997, 14, 175–194.
  11. Kaplan, R.; Kaplan, S. The Experience of Nature A Psychological Perspective; Cambridge University Press: Cambridge, UK, 1989.
  12. Neilson B, Craig C, Travis A, Sustainability MKV for, 2019 Undefined. A Review of the limitations of Attention Restoration Theory and the Importance of Its Future Research for the Improvement of Well-Being in Urban Living. 2019. Available online: https://www.ojs.unito.it/index.php/visions/issue/download/325/169#page=59 (accessed on 19 October 2022).
  13. Herzog, T.R.; Maguire, C.P.; Nebel, M.B. Assessing the restorative components of environments. J. Environ. Psychol. 2003, 23, 159–170.
  14. Kaplan, S. A Model of Person-Environment Compatibility. Environ. Behav. 1983, 15, 311–332.
  15. Amicone, G.; Petruccelli, I.; De Dominicis, S.; Gherardini, A.; Costantino, V.; Perucchini, P.; Bonaiuto, M. Green Breaks: The Restorative Effect of the School Environment’s Green Areas on Children’s Cognitive Performance. Front. Psychol. 2018, 9, 1579.
  16. Bai, X.; Li, X.; Yan, D. The Perceived Restorativeness of Outdoor Spatial Characteristics for High School Adolescents: A Case Study from China. Int. J. Environ. Res. Public Health 2022, 19, 7156.
  17. Jahncke, H.; Hygge, S.; Halin, N.; Green, A.M.; Dimberg, K. Open-plan office noise: Cognitive performance and restoration. J. Environ. Psychol. 2011, 31, 373–382.
  18. Lee, K.E.; Sargent, L.D.; Williams, N.S.; Williams, K.J. Linking green micro-breaks with mood and performance: Mediating roles of coherence and effort. J. Environ. Psychol. 2018, 60, 81–88.
  19. Bellini, D.; Bonaiuto, M.; Cubico, S. Exploring the Influence of Working Environments’ Restorative Quality on Organisational Citizenship Behaviours TIPPING+ Enabling Positive Tipping Points towards Clean-Energy Transitions in Coal and Carbon Intensive Regions View Project Flow-Identity (Positive Psychology) View Project. 2019. Available online: https://www.researchgate.net/publication/330122011 (accessed on 17 October 2022).
  20. Yusli, N.A.N.M.; Roslan, S.; Zaremohzzabieh, Z.; Ghiami, Z.; Ahmad, N. Role of Restorativeness in Improving the Psychological Well-Being of University Students. Front. Psychol. 2021, 12, 646329.
  21. Bakker, A.B.; Demerouti, E. The Job Demands-Resources model: State of the art. J. Manag. Psychol. 2007, 22, 309–328.
  22. Demerouti, E.; Bakker, A.B.; Nachreiner, F.; Schaufeli, W.B. The job demands-resources model of burnout. J. Appl. Psychol. 2001, 86, 499.
  23. Xanthopoulou, D.; Bakker, A.B.; Demerouti, E.; Schaufeli, W.B. Work engagement and financial returns: A diary study on the role of job and personal resources. J. Occup. Organ. Psychol. 2009, 82, 183–200.
  24. Kamaruddin, R.; Zainal, N.R.; Aminuddin, Z.M.; Jusoff, K. The Quality of Learning Environment and Academic Performance from a Student’s Perception. Int. J. Bus. Manag. 2009, 4, 171–175.
  25. Dormann, C.; Demerouti, E.; Bakker, A. A Model of Positive and Negative Learning: Learning demands and resources, learning engagement, critical thinking, and fake news detection. In Positive Learning in the Age of Information: A Blessing or a Curse? Springer VS: Wiesbaden, Germany, 2017; pp. 315–346.
  26. Schaufeli, W.B.; Taris, T.W. A critical review of the Job demands-resources model: Implications for improving work and health. In Bridging Occupational, Organizational and Public Health: A Transdisciplinary Approach; Bauer, F.G., Hämming, O., Eds.; Springer: Berlin/Heidelberg, Germany, 2014; pp. 43–68.
  27. Hobfoll, S.E.; Johnson, R.J.; Ennis, N.; Jackson, A.P. Resource Loss, Resource Gain, and Emotional Outcomes Among Inner City Women. J. Pers. Soc. Psychol. 2003, 84, 632–643.
  28. Bakker, A.B.; Demerouti, E. Job demands–resources theory: Taking stock and looking forward. J. Occup. Health Psychol. 2017, 22, 273–285.
  29. Bakker, A.B.; Demerouti, E. Job demands–resources theory. In Wellbeing: A Complete Reference Guide; Wiley: Hoboken, NJ, USA, 2014; pp. 1–28.
  30. Pelon, S.B. Compassion Fatigue and Compassion Satisfaction in Hospice Social Work. J. Soc. Work End-of-Life Palliat. Care 2017, 13, 134–150.
  31. Hobfoll, S.E. Conservation of Resources: A New Attempt at Conceptualizing Stress. Am. Psychol. 1989, 44, 513–524.
  32. Taris, T.W. Models in work and health research: The JDC(S), ERI and JD-R frameworks. In Research Handbook on Work and Well-Being; Edward Elgar Publishing: Cheltenham, UK, 2017; pp. 77–98.
  33. Bakker, A.B.; Demerouti, E.; Euwema, M.C. Job Resources Buffer the Impact of Job Demands on Burnout. J. Occup. Health Psychol. 2005, 10, 170–180.
  34. Einarsen, S.; Skogstad, A.; Rørvik, E.; Lande, B.; Nielsen, M.B. Climate for conflict management, exposure to workplace bullying and work engagement: A moderated mediation analysis. Int. J. Hum. Resour. Manag. 2016, 29, 549–570.
  35. Hakanen, J.J.; Schaufeli, W.B.; Ahola, K. The Job Demands-Resources model: A three-year cross-lagged study of burnout, depression, commitment, and work engagement. Work. Stress 2008, 22, 224–241.
  36. Cilliers, J.; Mostert, K.; Nel, J. Study demands, study resources and the role of personality characteristics in predicting the engagement of fist-year university students. South Afr. J. High. Educ. 2017, 32, 49–70.
  37. Brouwers, A.; Tomic, W.; Boluijt, H. Job demands, job control, social support and self-efficacy beliefs as determinants of burnout among physical education teachers. Eur. J. Psychol. 2011, 7, 17–39.
  38. Bailey, C.; Madden, A.; Alfes, K.; Fletcher, L. The Meaning, Antecedents and Outcomes of Employee Engagement: A Narrative Synthesis. Int. J. Manag. Rev. 2015, 19, 31–53.
  39. Mazzetti, G.; Robledo, E.; Vignoli, M.; Topa, G.; Guglielmi, D.; Schaufeli, W.B. Vibration reduction for structures: Distributed schemes over directed graphs. Psychol. Rep. 2019, 15, 2025–2042.
  40. Van Wingerden, J.; Derks, D.; Bakker, A.B. The Impact of Personal Resources and Job Crafting Interventions on Work Engagement and Performance. Hum. Resour. Manag. 2017, 56, 51–67.
  41. Bellini, D.; Fornara, F.; Bonaiuto, M. Positive environment in the workplace: The case of the mediating role of work engagement between restorativeness and job satisfaction/El entorno positivo en el ámbito laboral: El papel mediador del compromiso laboral entre la restauración y la satisfacción laboral. PsyEcology 2015, 6, 252–286.
  42. Pasanen, T.P.; Tyrväinen, L.; Korpela, K.M. The Relationship between Perceived Health and Physical Activity Indoors, Outdoors in Built Environments, and Outdoors in Nature. Appl. Psychol. Health Well-Being 2014, 6, 324–346.
  43. Tyrväinen, L.; Ojala, A.; Korpela, K.; Lanki, T.; Tsunetsugu, Y.; Kagawa, T. The influence of urban green environments on stress relief measures: A field experiment. J. Environ. Psychol. 2014, 38, 1–9.
  44. Csikszentmihalyi, M. Flow. The Psychology of Optimal Experience; HarperPerennial: New York, NY, USA, 1990; Available online: https://opus4.kobv.de/opus4-Fromm/frontdoor/index/index/docId/27641 (accessed on 18 October 2022).
  45. Csikszentmihalyi, M.; LeFevre, J. Optimal Experience in Work and Leisure. J. Pers. Soc. Psychol. 1989, 56, 815–822.
  46. European Flow-Researchers’ Network. What Is Flow—Current Definition. Available online: https://efrn.eu (accessed on 5 March 2022).
  47. Waterman, S. Predicting the Subjective Experience of Intrinsic Motivation: The Roles of Self-Determination, the Balance of Challenges and Skills, and Self-Realization Values. Personal. Soc. Psychol. Bull. 2003, 29, 1447–1458.
  48. Demerouti, E. Job characteristics, flow, and performance: The moderating role of conscientiousness. J. Occup. Health Psychol. 2006, 11, 266–280.
  49. Schüler, J. Arousal of Flow Experience in a Learning Setting and Its Effects on Exam Performance and Affect. Z. Pädagogische Psychol. 2007, 21, 217–227.
  50. Schüler, J.; Sheldon, K.M.; Fröhlich, S.M. Implicit need for achievement moderates the relationship between competence need satisfaction and subsequent motivation. J. Res. Personal. 2009, 44, 1–12.
  51. Busch, H.; Hofer, J.; Chasiotis, A.; Campos, D. The achievement flow motive as an element of the autotelic personality: Predicting educational attainment in three cultures. Eur. J. Psychol. Educ. 2013, 28, 239–254.
  52. Bressler, D.M.; Bodzin, A.M. Investigating Flow Experience and Scientific Practices During a Mobile Serious Educational Game. J. Sci. Educ. Technol. 2016, 25, 795–805.
  53. Heller, K.; Bullerjahn, C.; Von Georgi, R. The Relationship Between Personality Traits, Flow-Experience, and Different Aspects of Practice Behavior of Amateur Vocal Students. Front. Psychol. 2015, 6, 1901.
  54. Hamari, J.; Koivisto, J.; Sarsa, H. Does Gamification Work?—A Literature Review of Empirical Studies on Gamification. In Proceedings of the 47th Annual Hawaii International Conference on System Sciences, Waikoloa, HI, USA, 6–9 January 2014; pp. 3025–3034.
  55. Bakker, A.B. The work-related flow inventory: Construction and initial validation of the WOLF. J. Vocat. Behav. 2008, 72, 400–414.
  56. Craig, S.; Graesser, A.; Sullins, J.; Gholson, B. Affect and learning: An exploratory look into the role of affect in learning with AutoTutor. J. Educ. Media 2004, 29, 241–250.
  57. Salanova, M.; Bakker, A.B.; Llorens, S. Flow at Work: Evidence for an Upward Spiral of Personal and Organizational Resources*. J. Happiness Stud. 2006, 7, 1–22.
  58. Zito, M.; Cortese, C.G.; Colombo, L. Nurses’ exhaustion: The role of flow at work between job demands and job resources. J. Nurs. Manag. 2015, 24, E12–E22.
  59. Peifer, C.; Wolters, G.; Harmat, L.; Heutte, J.; Tan, J.; Freire, T.; Tavares, D.; Fonte, C.; Andersen, F.O.; van den Hout, J.; et al. A Scoping Review of Flow Research. Front. Psychol. 2022, 13, 815665.
  60. Manganelli, S.; Cavicchiolo, E.; Mallia, L.; Biasi, V.; Lucidi, F.; Alivernini, F. The interplay between self-determined motivation, self-regulated cognitive strategies, and prior achievement in predicting academic performance. Educ. Psychol. 2019, 39, 470–488.
  61. Bakar, R. The Effect of Learning Motivation on Student?s Productive Competencies in Vocational High School, West Sumatra. Int. J. Asian Soc. Sci. 2014, 4, 722–732.
  62. Marsh, H.W.; Martin, A. Academic self-concept and academic achievement: Relations and causal ordering. Br. J. Educ. Psychol. 2011, 81, 59–77.
  63. Christenson, S.L.; Wylie, C.; Reschly, A.L. Handbook of Research on Student Engagement; Springer: New York, NY, USA, 2012; pp. 1–840.
  64. Ryan, R.M.; Deci, E.L.; Vansteenkiste, M.; Soenens, B. Building a science of motivated persons: Self-determination theory’s empirical approach to human experience and the regulation of behavior. Motiv. Sci. 2021, 7, 97–110.
  65. Deci, E.L.; Ryan, R.M. The “What” and “Why” of Goal Pursuits: Human Needs and the Self-Determination of Behavior. Psychol. Inq. 2000, 11, 227–268.
  66. Ryan, R.M.; Deci, E.L. Self-Determination Theory: Basic Psychological Needs in Motivation, Development, and Wellness; Guilford Press: New York, NY, USA, 2017.
  67. Taylor, G.; Jungert, T.; Mageau, G.A.; Schattke, K.; Dedic, H.; Rosenfield, S.; Koestner, R. A self-determination theory approach to predicting school achievement over time: The unique role of intrinsic motivation. Contemp. Educ. Psychol. 2014, 39, 342–358.
  68. Froiland, J.M.; Worrell, F.C. Intrinsic motivation, learning goals, engagement, and achievement in a diverse high school. Psychol. Sch. 2016, 53, 321–336.
  69. Chau, S.; Cheung, C. Academic satisfaction with hospitality and tourism education in Macao: The influence of active learning, academic motivation, and student engagement. Asia Pac. J. Educ. 2018, 38, 473–487.
  70. Cho, S.; Lee, M.; Lee, S.M. Burned-Out Classroom Climate, Intrinsic Motivation, and Academic Engagement: Exploring Unresolved Issues in the Job Demand-Resource Model. Psychol. Rep. 2022, 1–22.
  71. Karimi, S.; Sotoodeh, B. The mediating role of intrinsic motivation in the relationship between basic psychological needs satisfaction and academic engagement in agriculture students. Teach. High. Educ. 2020, 25, 959–975.
  72. Steers, R.M.; Mowday, R.T.; Shapiro, D.L. The Future of Work Motivation Theory. Acad. Manag. Rev. 2004, 29, 379–387.
  73. Rheinber, F. Legacies in motivation science Heinz Heckhausen. Intrinsic Motivation and Flow. Motiv. Sci. 2020, 3, 199–200.
  74. Mouelhi-Guizani, S.; Guinoubi, S.; Chtara, M.; Crespo, M. Relationships between flow state and motivation in junior elite tennis players: Differences by gender. Int. J. Sports Sci. Coach. 2022.
  75. Mesurado, B.; Richaud, M.C.; Mateo, N.J. Engagement, Flow, Self-Efficacy, and Eustress of University Students: A Cross-National Comparison Between the Philippines and Argentina. J. Psychol. 2016, 150, 281–299.
  76. Plester, B.; Hutchison, A. Fun times: The relationship between fun and workplace engagement. Empl. Relations 2016, 38, 332–350.
  77. Csikszentmihalyi, M. Beyond Boredom and Anxiety: Experiencing Flow in Work and Play; The Jossey-Bass Behavioral Science Series; Jossey-Bass: Hoboken, NJ, USA, 1975.
  78. Buil, I.; Catalán, S.; Martínez, E. The influence of flow on learning outcomes: An empirical study on the use of clickers. Br. J. Educ. Technol. 2019, 50, 428–439.
  79. Ilies, R.; Wagner, D.; Wilson, K.; Ceja, L.; Johnson, M.; Derue, S.; Ilgen, D. Flow at Work and Basic Psychological Needs: Effects on Well-Being. Appl. Psychol. 2017, 66, 3–24.
  80. Csikszentmihalyi, M. Flow and the Foundations of Positive Psychology: The Collected Works of Mihaly Csikszentmihalyi; Springer: Dordrecht, The Netherlands, 2014; pp. 1–298.
  81. Kong, S.; Wang, Y. The influence of parental support and perceived usefulness on students’ learning motivation and flow experience in visual programming: Investigation from a parent perspective. Br. J. Educ. Technol. 2021, 52, 1749–1770.
  82. Wong, C.-S.; Hui, C.; Law, K.S. A longitudinal study of the job perception-job satisfaction relationship: A test of the three alternative specifications. J. Occup. Organ. Psychol. 1998, 71, 127–146.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
This entry is offline, you can click here to edit this entry!
ScholarVision Creations
Feedback