Control–Value Theory and Achievement Emotions: History
View Latest Version
Please note this is an old version of this entry, which may differ significantly from the current revision.
Contributor:
David William Putwain
,
Martin Daumiller

Control–value theory is a theoretical framework that integrates antecedents of achievement emotions with the motivational, information processing, and self-regulative effects of those emotions. Distal antecedents include the cultural, environmental, and social context of learning (e.g., school ethos and quality of instruction).

  • achievement emotions
  • control–value theory
  • network analysis
  • cost
  • enjoyment

1. Control–Value Theory

Proximal antecedents are subjective appraisals of control and value over achievement-related activities and outcomes. The emotions elicited through distal and proximal antecedents are not mere endpoints in themselves but have critical functional importance for motivation, information processing, and self-regulation. Specifically, of the three emotions included in the present study, enjoyment reinforces task activity and pride task outcomes and would, therefore, sustain high-quality motivation. Boredom, on the other hand, can undermine motivation due to absence of incentives. Furthermore, enjoyment can help to keep cognitive resources focused on the task and promote self-regulation of learning. Boredom, in contrast, promotes teacher-regulation of learning. Consequently, enjoyment and pride can promote, whereas boredom can disrupt, learning and achievement.

2. Control and Value Appraisals

Control appraisals include action–control expectations and action–outcome expectations. Action–control expectation is the prospective belief that one can initiate and perform an action that is similar to self-efficacy: the belief that one can successfully perform a specific action or task [1]. Action–outcome expectation is the prospective belief that actions will result in the expected outcomes. Control can also include retrospective attributions of success and failure to ability, oneself, effort, and so on [2][3].
Value appraisals include judgements over the intrinsic or extrinsic qualities of an activity or outcome. An activity or outcome is extrinsically valued when it is judged to contribute to the attainment of a desired outcome or goal (e.g., attain a target grade). Activities/outcomes are intrinsically valued when they are neither linked to any external contingency nor contribute to a desired goal (e.g., an activity could stimulate curiosity or be perceived as interesting). Value appraisals can also be positive or negative. Activities/outcomes that are desirable to perform or attain (e.g., success) are positively valued. Outcomes that are preferable to avoid (e.g., failure) or activities that are undesirable to perform (e.g., taking up too much time, or at the expense of other preferred alternates) are negatively valued.

3. Achievement Emotions

Achievement emotions are those experienced in relation to activities or outcomes that are judged against standards of competence [4]. Many, but not all, of the emotions experienced in relation to teaching, learning, and testing are captured by the aforementioned definition as they involve competence judgements that can be made by students themselves or others (e.g., teachers or examiners). In classroom settings, however, students may also experience social, epistemic, and topic-related emotions. Notwithstanding a degree of overlap, these emotions can be differentiated from achievement emotions as they do not focus on standards of competence per se. Achievement emotions can also be differentiated from moods, which are typically less intense and specific, but longer lasting, than emotions [5][6].
Discrete achievement emotions can be classified according to their valence (pleasant vs. unpleasant), activation (activating vs. deactivating), and focus (activity vs. outcome) [7][8]. In the present study, researchers considered three achievement emotions, namely enjoyment, boredom, and pride, as they are three of the emotions most commonly experienced in classroom settings [9]. The choice of these three emotions was determined partly by substantive concerns: to include a mixture of positive and negative, activity and outcome, and activating and deactivating emotions. In addition, to limit participant burden on relatively young participants, it was necessary to limit the number of items [10], hence the decision to measure only three emotions (no others were measured). In the above arrangement, enjoyment would be classified as a pleasant, activating, activity-focused emotion. Boredom would be classified as an unpleasant, deactivating, activity-focused emotion, and pride considered as a pleasant, activating, prospective-outcome-focused emotion.

4. Control–Value Appraisals and Enjoyment, Boredom, and Pride

According to CVT, a student will enjoy a learning activity if it is judged to be intrinsically or extrinsically useful (i.e., high value) and they are capable of performing that activity (i.e., high control). When a learning outcome is intrinsically or extrinsically valued (i.e., high value) and the student believes success is within their reach (i.e., high control), pride will arise. Boredom will arise when a learning activity is perceived as meaningless (i.e., the absence of value), or when task demands are judged as being too easy or too hard to ever succeed (i.e., very high or low control).
Numerous studies have supported these fundamental propositions of CVT regarding enjoyment, boredom, and pride, arising from control–value appraisals, using variable-centered analyses based on cross-sectional or longitudinal/prospective designs in students of all ages and stages of schooling. Pekrun et al. [3] and Bieleke et al. [11], for instance, found that control and value appraisals were positively related to enjoyment and pride, and negatively related to boredom, in samples of university students. The same pattern of correlations was shown for students in secondary education [12]. In samples of primary/elementary school students, the expected pattern of relations was shown for enjoyment and boredom [13][14]. Pride has yet to be examined for students in primary/elementary education. Furthermore, Loderer et al. [15] confirmed positive relations between enjoyment and control (r = 0.50) and value (r = 0.56) in a meta-analysis of 149 studies.
Although fewer studies have investigated how control–value appraisals interact to elicit enjoyment and pride, these too have supported CVT. In a sample of secondary students, Bieg et al. [16] found higher value to amplify the positive relation between control and pride. In university students, Goetz et al. [17] and Shao et al. [18] reported higher value to amplify the positive relations between control and enjoyment/pride. Putwain et al. [19][20] found higher value to amplify the positive relations between control and enjoyment in primary school students. Although not implied by CVT, control × value interactions for boredom were shown by Bieg et al. [16], Shao et al. [18], and Putwain et al. [20] such that boredom was maintained at higher control when combined with lower value.
Person-centered analyses to examine how emotions and control–value antecedents combine in clusters or profiles have not been widely used. In a notable exception, Parker et al. [21] used latent profile analysis to identify three clusters of enjoyment and boredom with control–value appraisals. In keeping with CVT, one profile comprised high control–value appraisals with high enjoyment and low boredom; the second profile comprised low control–moderate value with moderate enjoyment and high boredom; the third profile comprised moderate control–very low value with very low enjoyment and very high boredom.

5. Network Analysis

Network analysis (NA) is another analytic approach that could be used to examine achievement emotions alongside control–value antecedents. NA is a relatively novel approach that has been used in the mental health/psychopathology [22] and personality psychology [23] literature, but has not been widely used in the field of educational psychology. Notable exceptions from the field of educational psychology, described below, include Putwain et al. [24] and Tamura et al. [25]. NA is a variable-centered analysis that can establish how groups of items (referred to as nodes in NA) cohere as distinct communities, establish the relations between nodes (edges in the parlance of NA; typically based on semi-partial correlations) and the organization of nodes (or communities of nodes) within the entire network (i.e., the items included within a particular analysis), and whether certain edges bridge communities of items (referred to as bridge nodes).
Analyses can be represented graphically and with numerical indices [26]. The graphical network is instructive in showing the two-dimensional positioning of nodes. Nodes closer to the center of the network are more central and those further from the center are more peripheral; nodes placed adjacently are more closely related that those further apart. Numerical indices are helpful in identifying nodes with multiple and/or strong, direct and indirect, edges to others or those that link communities [27]. NA shares some similarities with multidimensional scaling analysis, which can be used to present correlations between items or constructs in a two-dimensional space such that highly correlated items/constructs are positioned more closely. NA differs in considering not only the position of nodes, but how they are directly and indirectly related, and whether specific nodes bridge communities of nodes.
Putwain et al. [24] examined a network comprised of test anxiety, generalized anxiety, panic disorder, and school-related wellbeing in a sample of adolescents. Nodes for the aforementioned constructs cohered into distinct communities and within test anxiety into respective cognitive and affective–physiological sub-communities. A generalized anxiety node for worry bridged communities of test anxiety, panic disorder, and the remaining generalized anxiety disorder nodes. Two other generalized anxiety nodes (both related to worry that something bad will happen) exhibited multiple strong links throughout the network.
Tamura et al. [25] used NA to examine relations between eight discrete emotions and control–value antecedents (along with other motivational constructs) in an experience-sampling study of four post-graduate researchers. Data collection involved daily prompts for single or two-item measures over a twelve-month period. In the study, students were also asked about the physical and psychological costs of their days’ work. Costs are analogous to the negative facet of value (i.e., high psychological and physical costs are desirable to avoid). In the emergent network, boredom was closely positioned to physical and psychological costs, and pride and happiness were most closely related to extrinsic values (i.e., the approval of others, aligning with personal values, and work obligations).
NA can offer a study of emotions and antecedents complementary to that of factor analysis and latent profile analysis by viewing emotions, and their antecedents, as an interconnected dynamic network. Specifically, as researchers have briefly demonstrated from these two brief examples, it will be possible to establish if nodes for discrete emotions and control–value antecedents cohere into distinct communities, establish the organization of those communities in a two-dimensional network, see which nodes show stronger and more numerous links to others, and see if specific nodes are bridging communities.

This entry is adapted from the peer-reviewed paper 10.3390/educsci13030239

References

  1. Bandura, A. Self-Efficacy: The Exercise of Control; Freeman: Philadelphia, PA, USA, 1997.
  2. Graham, S.; Taylor, A.Z. An attributional approach to emotional life in the classroom. In International Handbook of Emotions in Education; Pekrun, R., Linnenbrink-Garcia, L., Eds.; Routledge: London, UK, 2014; pp. 96–119.
  3. Weiner, B. The legacy of an attribution approach to motivation and emotion: A no-crisis zone. Motiv. Sci. 2018, 4, 4–14.
  4. Pekrun, R.; Perry, R.P. Control-value theory of achievement emotions. In International Handbook of Emotions in Education; Pekrun, R., Linnenbrink-Garcia, L., Eds.; Routledge: London, UK, 2014; pp. 120–141.
  5. Linnenbrink, E.A.; Pintrich, P.R. Achievement goal theory and affect: An asymmetrical bidirectional model. Educ. Psychol. 2002, 37, 69–78.
  6. Linnenbrink, E.A. Emotion research in education: Theoretical and methodological perspectives on the integration of affect, motivation and cognition. Educ. Psychol. Rev. 2006, 18, 307–314.
  7. Pekrun, R. Self-appraisals and emotions: A control-value approach. In Self—A Multidisciplinary Concept; Dicke, T., Guay, F., Marsh, H.W., Craven, R.G., McInerney, D.M., Eds.; Information Age Publishing: Charlotte, NC, USA, 2021.
  8. Pekrun, R.; Marsh, H.W.; Elliot, A.J.; Stockinger, K.; Perry, R.P.; Vogl, E.; Goetz, T.; van Tilburg, W.A.P.; Lüdtke, O.; Vispoel, W.P. A three-dimensional taxonomy of achievement emotions. J. Personal. Soc. Psychol. 2023, 124, 145–178.
  9. Pekrun, R.; Goetz, T.; Frenzel, A.C.; Barchfeld, P.; Perry, R.P. Measuring emotions in students’ learning and performance: The Achievement Emotions Questionnaire (AEQ). Contemp. Educ. Psychol. 2011, 36, 36–48.
  10. Kosovich, J.J.; Hulleman, C.S.; Barron, K.E. Measuring motivation in educational settings: A Case for pragmatic measurement. In The Cambridge Handbook on Motivation and Learning; Renninger, K.A., Hidi, S.E., Eds.; Cambridge University Press: Cambridge, MA, USA, 2019; pp. 713–738.
  11. Bieleke, M.; Gogol, K.; Goetz, T.; Pekrun, R. The AEQ-S: A short version of the Achievement Emotions Questionnaire. Contemp. Educ. Psychol. 2021, 65, 101940.
  12. Peixoto, F.; Mata, L.; Monteiro, V.; Sanches, C.; Pekrun, R. The Achievement Emotions Questionnaire: Validation for pre-adolescent students. Eur. J. Dev. Psychol. 2015, 12, 472–481.
  13. Lichtenfeld, S.; Pekrun, R.; Stupnisky, R.H.; Reiss, K.; Murayama, K. Measuring students’ emotions in the early years: The achievement emotions questionnaire-elementary school (AEQ-ES). Learn. Individ. Differ. 2012, 22, 190–201.
  14. Zaccoletti, S.; Altoé, G.; Mason, L. Enjoyment, anxiety and boredom, and their control-value antecedents as predictors of reading comprehension. Learn. Individ. Differ. 2020, 79, 101869.
  15. Loderer, K.; Pekrun, R.; Lester, J. Beyond cold technology: A systematic review and meta-analysis on emotions in technology-based learning environments. Learn. Instr. 2020, 70, 101162.
  16. Bieg, M.; Goetz, T.; Hubbard, K. Can I master it and does it matter? An intraindividual analysis on control–value antecedents of trait and state academic emotions. Learn. Individ. Differ. 2013, 28, 102–108.
  17. Goetz, T.; Frenzel, A.C.; Stoeger, H.; Hall, N.C. Antecedents of everyday positive emotions: An experience sampling analysis. Motiv. Emot. 2010, 34, 49–62.
  18. Shao, K.; Pekrun, R.; Marsh, H.W.; Loderer, K. Control-value appraisals, achievement emotions, and foreign language performance: A latent interaction analysis. Learn. Instr. 2020, 69, 101356.
  19. Putwain, D.W.; Schmitz, E.A.; Wood, P.; Pekrun, R. The role of achievement emotions in primary school mathematics: Control-value antecedents and achievement outcomes. Br. J. Educ. Psychol. 2021, 91, 347–367.
  20. Putwain, D.W.; Pekrun, R.; Nicholson, L.J.; Symes, W.; Becker, S.; Marsh, H.W. Control-value appraisals, enjoyment, and boredom in mathematics: A latent interaction analysis. Am. Educ. Res. J. 2018, 55, 1339–1368.
  21. Parker, P.C.; Perry, R.P.; Hamm Chipperfield, J.G.; Pekrun, R.; Dryden, R.P.; Daniels, L.M.; Tze, V.M.C. A motivation perspective on achievement appraisals, emotions, and performance in an online learning environment. Int. J. Educ. Res. 2021, 108, 101772.
  22. Fried, E.I.; van Borkulo, C.D.; Cramer, A.O.J.; Boschloo, L.; Schoevers, R.A.; Borsboom, D. Mental disorders as networks of problems: A review of recent insights. Soc. Psychiatry Psychiatr. Epidemiol. 2017, 52, 1–10.
  23. Heeren, A.; Bernstein, E.E.; McNally, R.J. Deconstructing trait anxiety: A network perspective. Anxiety Stress Coping 2018, 31, 262–276.
  24. Putwain, D.W.; Stockinger, K.; von der Embse, N.P.; Suldo, S.M.; Daumiller, M. Test anxiety, anxiety disorders, and school-related wellbeing: Manifestations of the same or different Constructs? J. Sch. Psychol. 2021, 88, 47–67.
  25. Tamura, A.; Ishii, R.; Yagi, A.; Fukuzumi, N.; Hatano, A.; Sakaki, M.; Tanaka, A.; Murayama, K. Exploring the within-person contemporaneous network of motivational engagement. Learn. Instr. 2022, 81, 101649.
  26. Epskamp, S.; Rhemtulla, M.T.; Borsboom, D. Generalized network psychometrics: Combining network and latent variable models. Psychometrika 2017, 82, 904–927.
  27. Robinaugh, D.J.; Millner, A.J.; McNally, R.J. Identifying highly influential nodes in the complicated grief network. J. Abnorm. Psychol. 2016, 125, 747–757.
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