Pre-Service Teachers’ Use of Technology to Learn to Teach: Exploring the Roles of Self-Efficacy,Resilience,and Academic Stress

Abstract

This exploratory study describes the distribution of pre-service teacher (PST) technology use for formal or informal professional learning. Additionally, it describes PSTs’ self-efficacy for technology use and associated factors. Laptops and smartphones were among the most commonly used devices. Technology use for professional learning was common in general but less so for informal learning. Modest levels of PST self-efficacy varied by activity, with lower levels of self-efficacy for informal learning. PSTs were particularly stressed due to examinations, workload, and lack of time to relax. Also, PSTs’ academic stress pertaining to performance pressures and time restraints was associated with greater technology use while academic stress pertaining to workload was associated with less technology use. Limitations and future directions are discussed.

Keywords

pre-service teachers technology self-efficacy resilience stress

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References

Admiraal

Van Vugt

Kranenburg

Koster

Smit

Weijers

Lockhorst

(2017). Preparing pre-service teachers to integrate technology into K–12 instruction: Evaluation of a technology-infused approach. Technology, Pedagogy and Education, 26(1), 105–120. https://doi.org/10.1080/1475939X.2016.1163283

Ajzen

(1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Bai

Ertmer

(2008). Teacher educators’ beliefs and technology uses as predictors of preservice teachers’ beliefs and technology attitudes. Journal of Technology and Teacher Education, 16(1), 93–112. https://doi.org/https://www.learntechlib.org/primary/p/22851/

Bakir

(2016). Technology and teacher education: A brief glimpse of the research and practice that have shaped the field. TechTrends, 60(1), 21–29. https://doi.org/10.1007/s11528-015-0013-4

Balakrishnan

Bahari

Paul

(2017). Impact of predisposing factors on academic stress among pre-service teachers. International Journal of Medical Research and Health Sciences, 3(4), 422–428. https://doi.org/10.36678/ijmaes.2017.v03i04.001

Bandura

(1997). Self-efficacy: The exercise of control. Macmillan.

Barahona

Nussbaum

Espinosa

Meneses

Alario-Hoyos

Pérez-Sanagustín

(2022). Transforming the learning experience in pre-service teacher training using the flipped classroom. Technology, Pedagogy and Education, 31(3), 261–274. https://doi.org/10.1080/1475939X.2022.2041476

Batane

Ngwako

(2017). Technology use by pre-service teachers during teaching practice: Are new teachers embracing technology right away in their first teaching experience? Australasian Journal of Educational Technology, 33(1), 48–61. https://doi.org/10.14742/ajet.2299

Bayrakdaroglu

Hekim

(2020). Examination of pre-service teachers’ stress levels towards academic expectations and goal commitment in terms of various variables. Asian Journal of Education and Training, 6(3), 461–467. https://doi.org/10.20448/journal.522.2020.63.461.467

10.

Bedewy

Gabriel

(2015). Examining perceptions of academic stress and its sources among university students: The perception of academic stress scale. Health Psychology Open, 2(2), 1–9. https://doi.org/10.1177/2055102915596714

11.

Bentler

P. M.

Bonett

D. G.

(1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. https://doi.org/10.1037/0033-2909.88.3.588

12.

Bergum Johanson

Leming

Johannessen

Solhaug

(2022). Competence in digital interaction and communication-A study of first-year preservice teachers’ competence in digital Interaction and communication at the start of their teacher education. The Teacher Educator, 58(3), 270–288. https://doi.org/10.1080/08878730.2022.2122095

13.

Brinkley-Etzkorn

(2020). The effects of training on instructor beliefs about and attitudes toward online teaching. American Journal of Distance Education, 34(1), 19–35. https://doi.org/10.1080/08923647.2020.1692553

14.

Brunetti

G. J.

(2006). Resilience under fire: Perspectives on the work of experienced, inner city high school teachers in the United States. Teaching and Teacher Education, 22(7), 812–825. https://doi.org/10.1016/j.tate.2006.04.027

15.

Brzycki

Dudt

(2005). Overcoming barriers to technology use in teacher preparation programs. Journal of Technology and Teacher Education, 13(4), 619–641. https://doi.org/www.learntechlib.org/primary/p/5167/

16.

Cavanagh

(2021). Pre-service teacher reflection and feedback using an online video platform during professional experience. Australian Journal of Teacher Education, 46(2), 72–85. https://doi.org/10.3316/aeipt.228955

17.

Chen

Lee

Tan

Wettasinghe

Wong

(2012). From device-centric to people-centric ubiquitous computing: Pre-service teachers using technology across spaces. Research and Practice in Technology Enhanced Learning, 7(1), 45–60. https://doi.org/https://rptel.apsce.net/index.php/RPTEL/article/view/2012-07004

18.

Colognesi

Hanin

(2024). Using digital technology in the classroom adds new professional tasks for (student) teachers. Technology, Pedagogy and Education, 33(2), 201–217. https://doi.org/10.1080/1475939X.2023.2293155

19.

Davis

F. D.

(1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

20.

Dede

(2006). Online professional development for teachers: Emerging models and methods. Harvard Education Press.

21.

Dede

Jass Ketelhut

Whitehouse

Breit

McCloskey

E. M.

(2009). A research agenda for online teacher professional development. Journal of Teacher Education, 60(1), 8–19. https://doi.org/10.1177/0022487108327554

22.

Delello

J. A.

(2014). Insights from pre-service teachers using science-based augmented reality. Journal of Computers in Education, 1(4), 295–311. https://doi.org/10.1007/s40692-014-0021-y

23.

DeMauro

A. A.

Jennings

P. A.

(2016). Pre-service teachers’ efficacy beliefs and emotional states. Emotional and Behavioural Difficulties, 21(1), 119–132. https://doi.org/10.1080/13632752.2015.1120057

24.

Duncan

H. E.

Barnett

(2009). Learning to teach online: What works for pre-service teachers. Journal of Educational Computing Research, 40(3), 357–376. https://doi.org/10.2190/EC.40.3.f

25.

Evers

W. J.

Brouwers

Tomic

(2002). Burnout and self-efficacy: A study on teachers’ beliefs when implementing an innovative educational system in The Netherlands. British Journal of Educational Psychology, 72(2), 227–243. https://doi.org/10.1348/000709902158865

26.

Farjon

Smits

Voogt

(2019). Technology integration of pre-service teachers explained by attitudes and beliefs, competency, access, and experience. Computers & Education, 130, 81–93. https://doi.org/10.1016/j.compedu.2018.11.010

27.

Francisco

M. J.

Quijano Jr

Pasoc

M. G.

Cruz

S. B. D.

Antes

Santos

M. D.

Abequibel

Deran

J. J.

Ricohermoso

Estigoy

Sarona

Marcial

Rillo

Alieto

Bećirović

(2022). Learning during the pandemic: Factors contributing to academic stress among special needs education pre-service teachers. Special Education, 1(43), 8057–8074. https://www.researchgate.net/publication/363229671_Learning_during_the_Pandemic_Factors_Contributing_to_Academic_Stress_among_Special_Needs_Education_Pre-Service_Teachers

28.

García-Martínez

Gavín-Chocano

León

S. P.

Ubago-Jiménez

J. L.

(2021a). Analysis of the pre-service teachers’ academic stress based on their self-concept and personality. Education Sciences, 11(11), 659. https://doi.org/10.3390/educsci11110659

29.

García-Martínez

Pérez-Navío

Pérez-Ferra

Quijano-López

(2021b). Relationship between emotional intelligence, educational achievement and academic stress of pre-service teachers. Behavioral Sciences, 11(7), 95. https://doi.org/10.3390/bs11070095

30.

Garcia

E. C.

Molins

L. L.

Fuertes-Alpiste

(2024). Online assessment practices during the pandemic in secondary schools in Catalonia. Technology, Pedagogy and Education, 33(4), 495–511. https://doi.org/10.1080/1475939X.2024.2342354

31.

Geng

Midford

Buckworth

(2015). Investigating the stress levels of early childhood, primary and secondary pre-service teachers during teaching practicum. Journal of Teacher Education for Sustainability, 17(1), 35–47. https://doi.org/10.1515/jtes-2015-0003

32.

Geng

Midford

Buckworth

(2016). Comparing stress levels of graduate and undergraduate pre-service teachers following their teaching practicums. Australian Journal of Teacher Education, 41(9), 100–116. https://doi.org/10.14221/ajte.2016v41n9.6

33.

Giles

(2019). The influence of paired grouping on teacher candidates’ attitude towards technology use and integration. Technology, Pedagogy and Education, 28(3), 363–380. https://doi.org/10.1080/1475939X.2019.1621772

34.

Han

Shin

(2017). The effect of student teaching experience and teacher beliefs on pre-service teachers’ self-efficacy and intention to use technology in teaching. Teachers and Teaching, 23(7), 829–842. https://doi.org/10.1080/13540602.2017.1322057

35.

(2009). Strength-based mentoring in pre-service teacher education: a literature review. Mentoring and Tutoring: Partnership in Learning, 17, 263–275. https://doi.org/10.1080/13611260903050205

36.

Hebert

Hickey

(2022). Preservice teachers during the COVID-19 pandemic: Concerns, preventive behaviors, and career intent. Education, 142(4), 188–196.

37.

Hodges

Moore

Lockee

Trust

Bond

(2020). The difference between emergency remote teaching and online learning. https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning.

38.

Howard

Johnson

(2004). Resilient teachers: Resisting stress and burnout. Social Psychology of Education, 7(4), 399–420. https://doi.org/10.1007/s11218-004-0975-0 .

39.

Bentler

P. M.

(1999). Cutoff criterion for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118

40.

Jimoyiannis

Koukis

(2023). Exploring teachers’ readiness and beliefs about emergency remote teaching in the midst of the COVID-19 pandemic. Technology, Pedagogy and Education, 32(2), 205–222. https://doi.org/10.1080/1475939X.2022.2163421

41.

Jones

Durham

Cataneo

(2021). Rising to the challenge: Preparing pre-service teachers during a global pandemic. The New Educator, 17(4), 375–393. https://doi.org/10.1080/1547688X.2021.1991538

42.

Joo

Y. J.

Park

Lim

(2018). Factors influencing preservice teachers’ intention to use technology: TPACK, teacher self-efficacy, and technology acceptance model. Journal of Educational Technology & Society, 21(3), 48–59. https://doi.org/http://www.jstor.com/stable/26458506

43.

Kent

A. M.

Giles

R. M.

(2017). Preservice teachers’ technology self-efficacy. SRATE Journal, 26(1), 9–20. https://doi.org/https://eric.ed.gov/?id=EJ1134392

44.

Klassen

R. M.

Chiu

M. M.

(2011). The occupational commitment and intention to quit of practicing and pre-service teachers: Influence of self-efficacy, job stress, and teaching context. Contemporary Educational Psychology, 36(2), 114–112. https://doi.org/10.1016/j.cedpsych.2011.01.002

45.

Kline

(2014). The new psychometrics: Science, psychology and measurement. Routledge.

46.

Koehler

M. J.

Mishra

(2009). What is technological pedagogical content knowledge? Contemporary Issues in Technology and Teacher Education, 9(1), 60–70. https://doi.org/www.learntechlib.org/primary/p/29544/

47.

Koh

Divaharan

(2011). Developing pre-service teachers’ technology integration expertise through the TPACK-developing instructional model. Journal of Educational Computing Research, 44(1), 35–58. https://doi.org/10.2190/EC.44.1.c

48.

Kush

J. M.

Badillo Goicoechea

Musci

R. J.

Stuart

E. A.

(2022). Teacher mental health during the COVID-19 pandemic. Educational Researcher, 51(9), 593–597. https://doi.org/10.3102/0013189X221134281

49.

Kyriacou

(2011). Teacher stress: From prevalence to resilience. In Langan-Fox

Cooper

C. L.

(Eds.), New horizons in management. Handbook of stress in the occupations (pp. 161–173). Edward Elgar Publishing.

50.

Le Cornu

(2009). Building resilience in pre-service teachers. Teaching and Teacher Education, 25(5), 717–723. https://doi.org/10.1016/j.tate.2008.11.016

51.

Le Cornu

(2013). Building early career teacher resilience: The role of relationships. Australian Journal of Teacher Education, 38(4), 1–16. https://doi.org/10.14221/ajte.2013v38n4.4

52.

Lemon

Garvis

(2016). Pre-service teacher self-efficacy in digital technology. Teachers and Teaching, 22(3), 387–408. https://doi.org/10.1080/13540602.2015.1058594

53.

Lundberg

C. A.

Kim

Y. K.

Andrade

L. M.

Bahner

D. T.

(2018). High expectations, strong support: Faculty behaviors predicting Latina/o community college student learning. Journal of College Student Development, 59(1), 55–70. https://doi.org/10.1353/csd.2018.0004

54.

Mansfield

Beltman

Weatherby-Fell

N. L.

(2020). I actually felt more confident”: An online resource for enhancing pre-service teacher resilience during professional experience. Australian Journal of Teacher Education, 45(4), 30–48. https://doi.org/10.14221/ajte.2020v45n4.3

55.

Mansfield

Papatraianou

McDonough

King

(2018). Building resilience in times of uncertainty and complexity: Teacher educator perceptions of pre-service teacher resilience. In Heck

Ambrosetti

(Eds.), Teacher education in and for uncertain times (1 ed., pp. 83–98). Springer. https://doi.org/10.1007/978-981-10-8648-9_6

56.

Marsh

H. W.

Hau

K. T.

Wen

(2004). In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler’s (1999) findings. Structural Equation Modeling: A Multidisciplinary Journal, 11(3), 320–341. https://doi.org/10.1207/s15328007sem1103_2

57.

Masten

A. S.

Best

K. M.

Garmezy

(1990). Resilience and development: Contributions from the study of children who overcome adversity. Development and Psychopathology, 2(4), 425–444. https://doi.org/10.1017/S0954579400005812

58.

McCorkle

L. S.

Coogle

C. G.

(2020). Technology-enhanced performance-based feedback in teacher preparation. Teacher Educators’ Journal, 13, 105–123. https://doi.org/https://eric.ed.gov/?id=EJ1247287

59.

McDonald

(1999). Test Theory: A unified treatment. Lawrence Erlbaum Associates.

60.

Meagher

Ozgün-Koca

S. A.

Edwards

M. T.

(2011). Preservice teachers’ experiences with advanced digital technologies: The interplay between technology in a preservice classroom and in field placements. Contemporary Issues in Technology and Teacher Education, 11(3), 243–270. https://doi.org/hwww.learntechlib.org/primary/p/36172/

61.

Merrick

Joseph

(2024). Innovations and illustrations of digital teaching practice in Australia during the pandemic: Variations on a theme. Technology, Pedagogy and Education, 33(4), 513–526. https://doi.org/10.1080/1475939X.2024.2336459

62.

Michos

Petko

(2024). Reflection using mobile portfolios during teaching internships: Tracing the influence of mentors and peers on teacher self-efficacy. Technology, Pedagogy and Education, 33(3), 291–311. https://doi.org/10.1080/1475939X.2024.2311798

63.

Newhouse

C. P.

Williams

P. J.

Pearson

(2006). Supporting mobile education for pre service teachers. Australasian Journal of Educational Technology, 22(3), 289–311. https://doi.org/10.14742/ajet.1288

64.

Newman-Thomas

Smith

C. A.

Zhao

Kethley

C. I.

Rieth

H. J.

Swanson

E. A.

Heo

(2012). Technology-based practice to teach preservice teachers to assess oral Reading fluency. Journal of Special Education Technology, 27(1), 15–32. https://doi.org/10.1177/016264341202700

65.

Olivier

Venter

(2003). The extent and causes of stress in teachers in the George region. South African Journal of Education, 23(3), 186–192. https://doi.org/https://hdl.handle.net/10520/EJC31947

66.

Ranellucci

Rosenberg

J. M.

Poitras

E. G.

(2020). Exploring pre-service teachers’ use of technology: The technology acceptance model and expectancy-value theory. Journal of Computer Assisted Learning, 36(6), 810–824. https://doi.org/10.1111/jcal.12459

67.

Richards

Levesque-Bristol

Templin

Graber

(2016). The impact of resilience on role stressors and burnout in elementary and secondary teachers. Social Psychology of Education, 19(3), 511–536. https://doi.org/10.1007/s11218-016-9346-x

68.

Richards

Templin

Gaudreault

(2013). Understanding the realities of school life: Recommendations for the preparation of physical education teachers. Quest (Grand Rapids, Mich), 65(4), 442–457. https://doi.org/10.1080/00336297.2013.804850

69.

Rosseel

(2012). Lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02

70.

Rubie-Davies

C. M.

Peterson

E. R.

Sibley

C. G.

Rosenthal

(2015). A teacher expectation intervention: Modelling the practices of high expectation teachers. Contemporary Educational Psychology, 40, 72–85. https://doi.org/10.1016/j.cedpsych.2014.03.003

71.

Sammons

Day

Kington

Stobart

Smees

(2007). Exploring variations in teachers’ work, lives and their effects on pupils: Key findings and implications from a longitudinal mixed-method study. British Educational Research Journal, 33(5), 681–701. https://doi.org/10.1080/01411920701582264

72.

Sánchez-Prieto

J. C.

Olmos-Migueláñez

García-Peñalvo

F. J.

(2017). MLearning and pre-service teachers: An assessment of the behavioral intention using an expanded TAM model. Computers in Human Behavior, 72, 644–654. https://doi.org/10.1016/j.chb.2016.09.061

73.

Santos Espino

Afonso Suárez

González-Henríquez

(2020). Video for teaching: Classroom use, instructor self-production and teachers’ preferences in presentation format. Technology, Pedagogy and Education, 29(2), 147–162. https://doi.org/10.1080/1475939X.2020.1726805

74.

Sasaki

Goff

Dowsett

Parossien

Matthies

Di Iorio

Montey

Rowe

Puddy

((2020). The practicum experience during COVID 19–supporting initial teacher education student’s practicum experience through a simulated classroom. Journal of Technology and Teacher Education, 28(2), 329–339. https://doi.org/www.learntechlib.org/primary/p/216244/

75.

Scherer

Tondeur

Siddiq

Baran

(2018). The importance of attitudes toward technology for pre-service teachers’ technological, pedagogical, and content knowledge: Comparing structural equation modeling approaches. Computers in Human Behavior, 80(2018), 67–80. https://doi.org/10.1016/j.chb.2017.11.003

76.

Schumacker

R. E.

Lomax

R. G.

(1996). A beginner’s guide to structural equation modeling. Lawrence Erlbaum.

77.

Skaalvik

E. M.

Skaalvik

(2010). Teacher self-efficacy and teacher burnout: A study of relations. Teaching and Teacher Education, 26(4), 1059–1069. https://doi.org/10.1016/j.tate.2009.11.001

78.

Smith

J. J.

Greene

H. C.

(2013). Pre-service teachers use e-learning technologies to enhance their learning. Journal of Information Technology Education: Research, 12(1), 121–140. https://doi.org/www.learntechlib.org/p/111353/

79.

Steiner

E. D.

Woo

(2022). Job-related stress threatens the teacher supply: Key findings from the 2021 State of the U.S. Teacher Survey. RAND Corporation.

80.

Taie

Lewis

(2022). Characteristics of 2020–21 public and private K–12 school teachers in the United States: Results from the National Teacher and Principal Survey First Look (NCES 2022-113). U.S. Department of Education. Washington, DC: National Center for Education Statistics. Retrieved from https://nces.ed.gov/pubsearch/pubsinfo.asp?pubid=2022113.

81.

Teichert

Piazza

(2023). Taking stock of teaching practice at the onset of COVID-19. Technology, Pedagogy and Education, 32(1), 117–132. https://doi.org/10.1080/1475939X.2022.2158923

82.

Teo

Noyes

(2014). Explaining the intention to use technology among pre-service teachers: A multi-group analysis of the unified theory of acceptance and use of technology. Interactive Learning Environments, 22(1), 51–66. https://doi.org/10.1080/10494820.2011.641674

83.

Teo

van Schaik

(2012). Understanding the intention to use technology by preservice teachers: An empirical test of competing theoretical models. International Journal of Human-Computer Interaction, 28(3), 178–188. https://doi.org/10.1080/10447318.2011.581892

84.

Thomas

Larson

Clift

Levin

(1996). Integrating technology in teacher education programs: Lessons from the teaching teleapprenticeship project. Action in Teacher Education, 17(4), 1–8. https://doi.org/10.1080/01626620.1996.10463347

85.

Tondeur

Aesaert

Prestridge

Consuegra

(2018). A multilevel analysis of what matters in the training of pre-service teacher's ICT competencies. Computers & Education, 122, 32–42. https://doi.org/10.1016/j.compedu.2018.03.002

86.

Tondeur

Pareja Roblin

van Braak

Voogt

Prestridge

(2017). Preparing beginning teachers for technology integration in education: Ready for take-off? Technology, Pedagogy and Education, 26(2), 157–177. https://doi.org/10.1080/1475939X.2016.1193556

87.

Venkatesh

Morris

M. G.

Davis

G. B.

Davis

F. D.

(2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

88.

Weatherby-Fell

Duchesne

Neilsen-Hewett

(2019). Preparing and supporting early childhood pre-service teachers in their professional journey. The Australian Educational Researcher, 46(4), 621–637. https://doi.org/10.1007/s13384-019-00340-4

89.

Wong

G. K.

(2015). Understanding technology acceptance in pre-service teachers of primary mathematics in Hong Kong. Australasian Journal of Educational Technology, 31(6), 713–735. https://doi.org/10.14742/ajet.1890

90.

Yada

Björn

P. M.

Savolainen

Kyttälä

Aro

Savolainen

(2021). Pre-service teachers’ self-efficacy in implementing inclusive practices and resilience in Finland. Teaching and Teacher Education, 105, 1–11. https://doi.org/10.1016/j.tate.2021.103398

91.

Wang

Zhai

Dai

Yang

(2015). The effect of work stress on job burnout among teachers: The mediating role of self-efficacy. Social Indicators Research, 122(3), 701–708. https://doi.org/10.1007/s11205-014-0716-5