Skip to main content
Log in

Cell phones and grades: examining mediation by perceived control and anxiety

  • Published:
Social Psychology of Education Aims and scope Submit manuscript

Abstract

Considerable evidence shows that cell phone use (CPU) is detrimental to students’ academic achievement. However, researchers have yet to consider whether or not perceived academic control (PAC) and anxiety can mediate this effect. In this two-semester study, we examined the role of PAC and learning-related anxiety in affecting the relationship between students’ daily CPU and their final grades in a university course. The study used a series of multiple regressions supplemented by the Hayes’ mediation procedures with a sample of first-year undergraduate students (N = 931) in a research-1 university. The results showed that PAC partially reduced the negative effects of CPU on the grades of the female students while the effects of CPU and PAC were virtually independent for the male students. Anxiety, in turn, did not mediate between CPU and the students’ academic performance for either females or males.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Ahmed, S., Pokhrel, N., Roy, S., & Samuel, A. J. (2019). Impact of nomophobia: A nondrug addiction among students of physiotherapy course using an online cross-sectional survey. Indian Journal of Psychiatry, 61(1), 77–80. https://doi.org/10.4103/psychiatry.IndianJPsychiatry_361_18.

    Article  Google Scholar 

  • Akram, R., & Mahmood, N. (2010). The relationship between test anxiety and academic achievement. Bulletin of Education and Research, 32(2), 63–74.

    Google Scholar 

  • Bai, R., Ma, Y., Liu, Y., Zhang, B., & Rasool, A. (2019). The relationship between cellphone use and achievement goals in junior high school students: A cross-lagged analysis. Psychology in the Schools, 56, 891–906. https://doi.org/10.1002/pits.22252.

    Article  Google Scholar 

  • Beranuy, M., Oberst, U., Carbonell, X., & Chamarro, A. (2009). Problematic Internet and mobile phone use and clinical symptoms in college students: The role of emotional intelligence. Computers in Human Behavior, 25(5), 1182–1187.

    Google Scholar 

  • Bhansali, R., & Trivedi, K. (2008). Is academic anxiety gender specific? A comparative study. Journal of Social Sciences, 17(1), 1–3.

    Google Scholar 

  • Bindu, P., & Thomas, I. (2006). Gender differences in emotional intelligence. Psychological Studies, 51, 261–268.

    Google Scholar 

  • Bisen, S., & Deshpande, Y. (2016). An analytical study of smartphone addiction among engineering students: A gender differences. The International Journal of Indian Psychology, 4(1), 70–83.

    Google Scholar 

  • Bollen, K. A., & Stine, R. (1990). Direct and indirect effects: Classical and bootstrap estimates of variability. Sociological Methodology, 20, 115–140.

    Google Scholar 

  • Brook, C., & Willoughby, T. (2015). The social ties that bind: Social anxiety and academic achievement across the university years. Journal of Youth and Adolescence, 44(5), 1139–1152. https://doi.org/10.1007/s10964-015-0262-8.

    Article  Google Scholar 

  • Carvalho, R. (2016). Gender differences in academic achievement: The mediating role of personality. Personality and Individual Differences, 94, 54–58. https://doi.org/10.1016/j.paid.2016.01.011.

    Article  Google Scholar 

  • Cassady, J. C., & Johnson, R. E. (2002). Cognitive test anxiety and academic procrastination. Contemporary Educational Psychology, 27, 270–295.

    Google Scholar 

  • Cheema, J. R. (2014). Some general guidelines for choosing missing: Data handling methods in educational research. Journal of Modern Applied Statistical Methods, 13(2), 53–75. https://doi.org/10.22237/jmasm/1414814520.

    Article  Google Scholar 

  • Chipperfield, J. G. (1993). Perceived barriers in coping with health problems: A 12-year longitudinal study of survival among elders. Journal of Aging and Health, 5(1), 123–139. https://doi.org/10.1177/089826439300500106.

    Article  Google Scholar 

  • Chipperfield, J. G., Hamm, J. M., Perry, R. P., & Ruthig, J. C. (2017). Perspectives on studying perceived control in the twenty-first century. In M. D. Robinson & M. Eid (Eds.), The happy mind: Cognitive contributions to well-being (pp. 215–233). Cham: Springer. https://doi.org/10.1007/978-3-319-58763-9_12

    Chapter  Google Scholar 

  • Chipperfield, J. G., Newall, N. E., Perry, R. P., Bailis, D. S., Stewart, T. L., & Ruthig, J. C. (2012a). Sense of control in late life: Health and survival implications. Personality and Social Psychology Bulletin, 38(8), 1081–1092. https://doi.org/10.1177/0146167212444758.

    Article  Google Scholar 

  • Chipperfield, J. G., Perry, R. P., & Stewart, T. L. (2012b). Perceived control. In Encyclopedia of human behavior, 2nd ed. Elsevier https://doi.org/10.1016/B978-0-12-375000-6.00109-9.

  • Dos, B. (2014). The relationship between mobile phone use, metacognitive awareness and academic achievement. European Journal of Educational Research, 3(4), 192–200.

    Google Scholar 

  • Elhai, J. D., Dvorak, R. D., Levine, J. C., & Hall, B. J. (2017). Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology. Journal of Affective Disorders, 207, 251–259.

    Google Scholar 

  • Farooqui, I. A., Pore, P., & Gothankar, J. (2018). Nomophobia: An emerging issue in medical institutions? Journal of Mental Health, 27(5), 438–441. https://doi.org/10.1080/09638237.2017.1417564.

    Article  Google Scholar 

  • Fernández-Berrocal, P., Extremera, N., & Ramos, N. (2004). Validity and reliability of the Spanish modified version of the Trait Meta-Mood Scale. Psychological Reports, 94, 751–755.

    Google Scholar 

  • Frangos, C. C., Frangos, C. C., & Kiohos, A. P. (2010). Internet addiction among Greek university students: Demographic associations with the phenomenon, using the Greek version of young’s internet addiction test. International Journal of Economic Sciences and Applied Research, 3(1), 49–74.

    Google Scholar 

  • Fredrik, S., Michael, C., & Lennart, H. (2008). Use of wireless telephones and self-reported health symptoms: A population-based study among Swedish adolescents aged 15–19 years. Environmental Health: A Global Access Science Source, 7(18), 1–10.

    Google Scholar 

  • Garber, J., & Seligman, M. (1980). Human helplessness: Theory and applications. New York: Academic Press.

    Google Scholar 

  • Giunchiglia, F., Zeni, M., Zeni, E., Bignotti, E., & Bison, I. (2018). Mobile social media usage and academic performance. Computers in Human Behavior, 82, 177–185. https://doi.org/10.1016/j.chb.2017.12.041.

    Article  Google Scholar 

  • Gutiérrez-Puertas, L., Márquez-Hernández, V., Gutiérrez-Puertas, V., Granados-Gámez, G., & Aguilera-Manrique, G. (2020). The effect of cell phones on attention and learning in nursing students. CIN: Computers, Informatics, Nursing. https://doi.org/10.1097/CIN.0000000000000626.

    Article  Google Scholar 

  • Goldenberg, I., Matheson, K., & Mantler, J. (2006). The assessment of emotional intelligence: A comparison of performance-based and self-report methodologies. Journal of Personality Assessment, 86, 33–34.

    Google Scholar 

  • Gomez-Baya, D., Malesdoza, R., Paino, S., & Matos, M. G. (2017). Perceived emotional intelligence as a predictor of depressive symptoms during mid-adolescence: A two-year longitudinal study on gender differences. Personality and Individual Differences, 104, 303–312.

    Google Scholar 

  • Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data analysis (7th ed.). New York: Pearson.

    Google Scholar 

  • Hamm, J., Kamin, S., Chipperfield, J., Perry, R., & Lang, F. (2019). The detrimental consequences of overestimating future health in late life. The Journals of Gerontology: Series B, 74(3), 373–381. https://doi.org/10.1093/geronb/gbx074.

    Article  Google Scholar 

  • Hamm, J., Perry, R., Chipperfield, J., Hladkyj, S., Parker, P., & Weiner, B. (2020). Reframing achievement setbacks: A motivation intervention to improve 8-year graduation rates for students in Science, Technology, Engineering, and Mathematics (STEM) fields. Psychological Science. https://doi.org/10.1177/0956797620904451.

    Article  Google Scholar 

  • Hamm, J. M., Perry, R. P., Clifton, R. A., Chipperfield, J. G., & Boese, G. D. (2014). Attributional retraining: A motivation treatment with differential psychosocial and performance benefits for failure prone individuals in competitive achievement settings. Basic and Applied Social Psychology, 36(3), 221–237.

    Google Scholar 

  • Hembree, R. (1988). Correlates, causes, effects, and treatment of test anxiety. Review of Educational Research, 58(1), 47–77. https://doi.org/10.2307/1170348.

    Article  Google Scholar 

  • Hoffman, J., & Lowitzki, K. (2005). Predicting college success with high school grades and test scores: Limitations for minority students. The Review of Higher Education, 28(4), 455–474.

    Google Scholar 

  • Hong, F. Y., Chiu, S. I., & Huang, D. H. (2012). A model of the relationship between psychological characteristics, mobile phone addiction and use of mobile phones by Taiwanese university female students. Computers in Human Behavior, 28, 2152–2159.

    Google Scholar 

  • Hossain, M. (2019). Impact of mobile phone usage on academic performance. World Scientific News, 118, 164–180.

    Google Scholar 

  • Iacobucci, D., Posavac, S. S., Kardes, F. R., Schneider, M. J., & Popovich, D. L. (2015). The median split: Robust, refined, and revived. Journal of Consumer Psychology. https://doi.org/10.1016/j.jcps.2015.06.014.

    Article  Google Scholar 

  • Jenaro, C., Flores, N., Gómez-Vela, M., González-Gil, F., & Caballo, C. (2007). Problematic internet and cell-phone use: Psychological, behavioral, and health correlates. Addiction Research & Theory, 15(3), 309–320. https://doi.org/10.1080/16066350701350247.

    Article  Google Scholar 

  • Junco, R., & Cotton, S. R. (2012). No A 4 U: The relationship between multitasking and academic performance. Computers & Education, 59, 505–514.

    Google Scholar 

  • Kates, A. W., Wu, H., & Coryn, C. L. S. (2018). The effects of mobile phone use on academic performance: A meta-analysis. Computers & Education, 127, 107–112. https://doi.org/10.1016/j.compedu.2018.08.012.

    Article  Google Scholar 

  • Lee, S., Kim, M. W., Mcdonough, I. M., Mendoza, J. S., & Kim, M. S. (2017). The effects of cell phone use and emotion-regulation style on college students’ learning. Applied Cognitive Psychology, 31, 360–366.

    Google Scholar 

  • Lepp, A., Barkley, J., & Karpinski, A. (2014). The relationship between cell phone use, academic performance, anxiety, and satisfaction with life in college students. Computers in Human Behavior, 31(1), 343–350. https://doi.org/10.1016/j.chb.2013.10.049.

    Article  Google Scholar 

  • Levine, L. E., Waite, B. M., & Bowman, L. L. (2007). Electronic media use, reading, and academic distractibility in college youth. Cyber Psychology and Behavior, 10, 560–566.

    Google Scholar 

  • Li, J., Lepp, A., & Barkley, J. (2015). Locus of control and cell phone use: Implications for sleep quality, academic performance, and subjective well-being. Computers in Human Behavior, 52, 450–457. https://doi.org/10.1016/j.chb.2015.06.021.

    Article  Google Scholar 

  • MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D. (2002). On the practice of dichotomization of quantitative variables. Psychological Methods, 7(1), 19–40. https://doi.org/10.1037//1082-989X.7.1.19.

    Article  Google Scholar 

  • Maxey, E. J., & Ormsby, V. J. (1971). The accuracy of self-report information collected on the ACT test battery: High school grades and items of nonacademic achievement (ACT research report 45). Iowa City: The Research and Development Division.

    Google Scholar 

  • Merlo, L. (2008). Increased cell phone use may heighten symptoms of anxiety. Primary Psychiatry, 15(5), 27–28.

    Google Scholar 

  • Meyer, G. J., Finn, S. E., Eyde, L. D., Kay, G. G., Moreland, K. L., Dies, R. R., et al. (2001). Psychological testing and psychological assessment: A review of evidence and issues. In A. E. Kazdin (Ed.), Methodological issues and strategies in clinical research (Vol. 3, pp. 265–345). Washington, DC: American Psychological Association.

    Google Scholar 

  • Nayak, J. (2018). Relationship among smartphone usage, addiction, academic performance and the moderating role of gender: A study of higher education students in India. Computers & Education, 123, 164–173. https://doi.org/10.1016/j.compedu.2018.05.007.

    Article  Google Scholar 

  • Núñez-Peña, M. I., Suárez-Pellicioni, M., & Bono, R. (2013). Effects of math anxiety on student success in higher education. International Journal of Educational Research, 58, 36–43. https://doi.org/10.1016/j.ijer.2012.12.004.

    Article  Google Scholar 

  • Parker, P. C., Perry, R. P., Chipperfield, J. G., Hamm, J. M., & Pekrun, R. (2017). An attribution-based motivation treatment for low control students who are bored in online learning environments. Motivation Science. https://doi.org/10.1037/mot0000081.

    Article  Google Scholar 

  • Parker, P. C., Perry, R. P., Hamm, J. M., Chipperfield, J. G., & Hladkyj, S. (2016). Enhancing the academic success of competitive student athletes using a motivation treatment intervention (attributional retraining). Psychology of Sport and Exercise, 26, 113–122.

    Google Scholar 

  • Parker, P. C., Perry, R. P., Hamm, J. M., Chipperfield, J. G., Hladkyj, S., & Leboe-McGowan, L. (2018). Attribution-based motivation treatment efficacy in high-stress student athletes: A moderated-mediation analysis of cognitive, affective, and achievement processes. Psychology of Sport and Exercise, 35, 189–197.

    Google Scholar 

  • Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review, 18, 315–341.

    Google Scholar 

  • Pekrun, R., Goetz, T., Frenzel, A., Barchfeld, P., & Perry, R. (2011). Measuring emotions in students’ learning and performance: The Achievement Emotions Questionnaire (AEQ). Contemporary Educational Psychology, 36(1), 36–48. https://doi.org/10.1016/j.cedpsych.2010.10.002.

    Article  Google Scholar 

  • Pekrun, R., Goetz, T., & Perry, R. P. (2005). Achievement Emotions Questionnaire (AEO). User's manual. Department of Psychology, University of Munich, Munich, Germany.

  • Pekrun, R., & Linnenbrink-Garcia, L. (2014). International handbook of emotions in education. New York: Routledge. https://doi.org/10.4324/9780203148211.

    Book  Google Scholar 

  • Pekrun, R., & Stephens, E. J. (2015). Test anxiety and academic achievement. In J. D. Wright (Ed.), International encyclopedia of the social & behavioral sciences, 2nd ed. (pp. 244–249). https://doi.org/10.1016/B978-0-08-097086-8.26064-9.

  • Perry, R. P. (2003). Perceived (academic) control and causal thinking in achievement settings. Canadian Psychology, 44(4), 312–331.

    Google Scholar 

  • Perry, R. P., Chipperfield, J. G., Hladkyj, S., Pekrun, R., & Hamm, J. M. (2014). Attribution-based treatment interventions in achievement settings. In S. Karabenick & T. Urdan (Eds.), Advances in motivation and achievement (Vol. 18). Bingley: Emerald Publishing.

    Google Scholar 

  • Perry, R. P., Hall, N. C., & Ruthig, J. C. (2005a). Perceived (academic) control and scholastic attainment in higher education. In J. Smart (Ed.), Higher education: Handbook of theory and research (Vol. 20, pp. 363–436). Amsterdam: Springer.

    Google Scholar 

  • Perry, R. P., & Hamm, J. M. (2017). An attribution perspective on competence and motivation: Theory and application. In A. Elliot, C. Dweck, & D. Yeager (Eds.), Handbook of competence and motivation: Theory and applications (2nd ed., pp. 61–84). New York: Gilford Press.

    Google Scholar 

  • Perry, R. P., Hladkyj, S., Pekrun, R. H., Clifton, R. A., & Chipperfield, J. G. (2005b). Perceived academic control and failure in college students: A three-year study of scholastic attainment. Research in Higher Education, 46, 535–569. https://doi.org/10.1007/s11162-005-3364-4.

    Article  Google Scholar 

  • Perry, R. P., Hladkyj, S., Pekrun, R. H., & Pelletier, S. T. (2001). Academic control and action control in the achievement of college students: A longitudinal field study. Journal of Educational Psychology, 93, 776–789. https://doi.org/10.1037/0022-0663.93.4.776.

    Article  Google Scholar 

  • Perry, S., & Lee, K. (2007). Mobile phone text messaging overuse among developing world university students. Communication, 33(2), 63–79. https://doi.org/10.1080/02500160701685417.

    Article  Google Scholar 

  • Pierce, T. (2009). Social anxiety and technology: Face-to-face communication versus techno-logical communication among teens. Computers in Human Behavior, 25, 1367–1372. https://doi.org/10.1016/j.chb.2009.06.003.

    Article  Google Scholar 

  • Prasad, M., Patthi, B., Singla, A., Gupta, R., Saha, S., Kumar, J. K., et al. (2017). Nomophobia: A cross-sectional study to assess mobile phone usage among dental students. Journal of Clinical and Diagnostic Research: JCDR, 11(2), ZC34–ZC39. https://doi.org/10.7860/JCDR/2017/20858.9341.

    Article  Google Scholar 

  • Respondek, L., Seufert, T., Hamm, J., & Nett, U. (2019). Linking changes in perceived academic control to university dropout and university grades: A longitudinal approach. Journal of Educational Psychology. https://doi.org/10.1037/edu0000388.

    Article  Google Scholar 

  • Respondek, L., Seufert, T., Stupnisky, R., & Nett, U. E. (2017). Perceived academic control and academic emotions predict undergraduate university student success: Examining effects on dropout intention and achievement. Frontiers in Psychology, 8, 243. https://doi.org/10.3389/fpsyg.2017.00243.

    Article  Google Scholar 

  • Rodin, J. (1986). Aging and health: Effects of the sense of control. Science, 233(4770), 1271–1276. https://doi.org/10.1126/science.3749877.

    Article  Google Scholar 

  • Rodríguez-García, A. M., Moreno-Guerrero, A. J., & López Belmonte, J. (2020). Nomophobia: An individual's growing fear of being without a smartphone-a systematic literature review. International Journal of Environmental Research and Public Health, 17(2), 580. https://doi.org/10.3390/ijerph17020580.

    Article  Google Scholar 

  • Rosen, L. D., Whaling, K., Rab, S., Carrier, L. M., & Cheever, N. A. (2013). Is Facebook creating “iDisorders”? The link between clinical symptoms of psychiatric disorders and technology use, attitudes and anxiety. Computers in Human Behavior, 29, 1243–1254. https://doi.org/10.1016/j.chb.2012.11.012.

    Article  Google Scholar 

  • Ruthig, J. C., Perry, R. P., Hladkyj, S., Hall, N. C., Pekrun, R., & Chipperfield, J. G. (2008). Perceived control and emotions: Interactive effects on performance in achievement settings. Social Psychology of Education, 11(2), 161–180.

    Google Scholar 

  • Salovey, P., Mayer, J. D., Goldman, S. L., Turvey, C., & Palfai, T. P. (1995). Emotional attention, clarity, and repair: Exploring emotional intelligence using Trait Meta-Mood Scale. In J. W. Pennebacker (Ed.), Emotion, disclosure, & health (pp. 125–154). Washington, DC: American Psychological Association.

    Google Scholar 

  • Seo, D. G., Park, Y., Kim, M. K., & Park, J. (2016). Mobile phone dependency and its impacts on adolescents’ social and academic behaviors. Computers in Human Behavior, 63, 282–292. https://doi.org/10.1016/j.chb.2016.05.026.

    Article  Google Scholar 

  • Shrout, P. E., & Bolger, N. (2002). Mediation in experimental and nonexperimental studies: New procedures and recommendations. Psychological Methods, 7, 422–445.

    Google Scholar 

  • Smith, S. T. (2018). Cell phone distraction, human factors, and litigation (2nd ed.). Tucson, AZ: Lawyers & Judges Publishing Company Inc.

    Google Scholar 

  • Spangler, G., Pekrun, R., Kramer, K., & Hofmann, H. (2002). Students' emotions, physiological reactions, and coping in academic exams. Anxiety, Stress, and Coping, 15(4), 413–432.

    Google Scholar 

  • Steinmayr, R., Spinath, B., & Johnson, W. (2008). Sex differences in school achievement: What are the roles of personality and achievement motivation? European Journal of Personality, 22(3), 185–209. https://doi.org/10.1002/per.676.

    Article  Google Scholar 

  • Stewart, T., Chipperfield, J., Perry, R., & Hamm, J. (2016). Attributing heart attack and stroke to “Old Age”: Implications for subsequent health outcomes among older adults. Journal of Health Psychology, 21(1), 40–49. https://doi.org/10.1177/1359105314521477.

    Article  Google Scholar 

  • Stupnisky, R., Perry, R., Renaud, R., & Hladkyj, S. (2013). Looking beyond grades: Comparing self-esteem and perceived academic control as predictors of first-year college students’ well-being. Learning and Individual Differences, 23, 151–157. https://doi.org/10.1016/j.lindif.2012.07.008.

    Article  Google Scholar 

  • Sticca, F., Goetz, T., Bieg, M., Hall, N. C., Eberle, F., & Haag, L. (2017). Examining the accuracy of students’ self-reported academic grades from a correlational and a discrepancy perspective: Evidence from a longitudinal study. PLoS ONE, 12(11), e0187367. https://doi.org/10.1371/journal.pone.0187367.

    Article  Google Scholar 

  • Sung, Y., Chang, K., & Liu, T. (2016). The effects of integrating mobile devices with teaching and learning on students’ learning performance: A meta-analysis and research synthesis. Computers & Education, 94, 252–275. https://doi.org/10.1016/j.compedu.2015.11.008.

    Article  Google Scholar 

  • Tarantino, J. (2019). Effects of cell phones on student lecture note taking and test taking performance. Doctoral dissertation, Columbia University, New York, USA. https://doi.org/10.7916/d8-n42r-p468.

  • Thomas, C., Cassady, J., & Heller, M. (2017). The influence of emotional intelligence, cognitive test anxiety, and coping strategies on undergraduate academic performance. Learning and Individual Differences, 55, 40–48. https://doi.org/10.1016/j.lindif.2017.03.001.

    Article  Google Scholar 

  • Van Deursen, A., Bolle, C., Hegner, S., & Kommers, P. (2015). Modeling habitual and addictive smartphone behavior: The role of smartphone usage types, emotional intelligence, social stress, self-regulation, age, and gender. Computers in Human Behavior, 45, 411–420. https://doi.org/10.1016/j.chb.2014.12.039.

    Article  Google Scholar 

  • Wang, M., Shen, R., Novak, D., & Pan, X. (2009). The impact of mobile learning on students’ learning behaviors and performance: Report from a large blended classroom. British Journal of Educational Technology, 40, 673–695.

    Google Scholar 

  • Weiner, B. (2007). Examining emotional diversity in the classroom: An attribution theorist considers the moral emotions. In P. A. Schutz & R. Pekrun (Eds.), Emotion in education (pp. 75–88). San Diego, CA: Academic Press. https://doi.org/10.1016/B978-012372545-5/50006-X

    Chapter  Google Scholar 

  • Wentworth, D., & Middleton, J. H. (2014). Technology use and academic performance. Computers & Education, 78, 306–311. https://doi.org/10.1016/j.compedu.2014.06.012.

    Article  Google Scholar 

  • Wood, E., Zivcakova, L., Gentile, P., Archer, K., De Pasquale, D., & Nosko, A. (2011). Examining the impact of off-task multi-tasking with technology on real-time classroom learning. Computers & Education, 58, 365–374.

    Google Scholar 

  • Yildirim, C., & Correia, A. (2015). Exploring the dimensions of nomophobia: Development and validation of a self-reported questionnaire. Computers in Human Behavior, 49, 130–137. https://doi.org/10.1016/j.chb.2015.02.059.

    Article  Google Scholar 

  • Zeidner, M., & Matthews, G. (2005). Evaluation anxiety. In A. J. Elliot & C. S. Dweck (Eds.), Handbook of competence and motivation (pp. 141–163). London: Guildford Press.

    Google Scholar 

Download references

Acknowledgements

This research was supported by grants to R. P. Perry from the Social Sciences and Humanities Research Council of Canada (SSHRC) Insight program (435-2017-804) and the Royal Society of Canada, and to J. G. Chipperfield from SSHRC (435-2016-970).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Masha V. Krylova.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Krylova, M.V., Dryden, R.P., Perry, R.P. et al. Cell phones and grades: examining mediation by perceived control and anxiety. Soc Psychol Educ 23, 1277–1301 (2020). https://doi.org/10.1007/s11218-020-09581-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11218-020-09581-z

Keywords

Navigation