The reliability of test scores is not a fixed property of an instrument but may vary across populations and testing conditions. Evaluating how a scale performs across different samples is essential for understanding the extent of measurement error and generalizing psychometric properties. In the present study, Bandura’s Self-Efficacy for Self-Regulated Learning Scale (SESRLS) was examined using a reliability generalization meta-analysis to assess the generalizability of Cronbach’s alpha across studies. A random-effects model was employed to compute the pooled mean reliability coefficient. In addition, meta-regression was conducted to investigate the impact of study characteristics—both substantive and methodological—on reliability. Moderator variables included categorical factors (age group, mode of administration, test language, region, item type) and continuous variables (mean age, age standard deviation, percentage of females, sample size, number of response options, and number of items). The analysis synthesized 78 alpha coefficients derived from a total sample of 32,116 participants. Bonett’s transformation was applied to stabilize sampling variances associated with bounded reliability estimates. Results revealed that mean raw alpha was .85 (95% CI [.837–.857]) and pooled mean alpha was .869 (95% CI [.857–.884]) for transformed scores. Substantial heterogeneity was detected (I2 = 97.6%). Of all moderators examined, only test language significantly predicted reliability coefficients (β = −0.221, p = .047), with slightly higher values reported in non-English versions. No other moderator variables were found to exert a significant influence. These findings support the generalizability of the SESRLS’s reliability estimates across diverse demographic and methodological contexts, while highlighting the need to consider the rigor and quality of the adaptation process in reliability reporting.
AcarS.LeeL. E.SchererR. (2024). A reliability generalization of the torrance tests of creative thinking-figural. European Journal of Psychological Assessment, 40(5), 396–411. https://doi.org/10.1027/1015-5759/a000819
2.
BanduraA. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.
3.
BanduraA. (1989). The multidimensional self-efficacy scales. Stanford University. [Unpublished instrument].
4.
BanduraA. (2006). Guide for constructing self-efficacy scales. In PajaresF.UrdanT. (Eds.), Self-efficacy beliefs of adolescents, (Vol. 5, pp. 307–337). Information Age Publishing.
5.
BatıK.IrmakŞ. (2024). A reliability generalization study of the STEM-CIS scale: Exploring moderator effects. Current Psychology, 43(46), 35453–35470. https://doi.org/10.1007/s12144-024-07036-8
6.
BeretvasS. N.PastorD. A. (2003). Using mixed-effects models in reliability generalization studies. Educational and Psychological Measurement, 63(1), 75–95. https://doi.org/10.1177/0013164402239318
7.
BonettD. G. (2002). Sample size requirements for estimating intraclass correlations with desired precision. Statistics in Medicine, 21(9), 1331–1335. https://doi.org/10.1002/sim.1108
8.
BonettD. G. (2020). Point‐biserial correlation: Interval estimation, hypothesis testing, meta‐analysis, and sample size determination. British Journal of Mathematical and Statistical Psychology, 73(Suppl 1), 113–144. https://doi.org/10.1111/bmsp.12189
9.
CapraraG. V.FidaR.VecchioneM.Del BoveG.VecchioG. M.BarbaranelliC.BanduraA. (2008). Longitudinal analysis of the role of perceived self-efficacy for self-regulated learning in academic continuance and achievement. Journal of Educational Psychology, 100(3), 525–534. https://doi.org/10.1037/0022-0663.100.3.525
10.
CapraraG. V.VecchioneM.AlessandriG.GerbinoM.BarbaranelliC. (2011). The contribution of personality traits and self-efcacy beliefs to academic achievement: A longitudinal study. British Journal of Educational Psychology, 81(1), 78–96. https://doi.org/10.1348/2044-8279.002004
11.
ChatrakamollathasS.MohaK. P.ChoochomO. (2022). Academic procrastination behavior among college undergraduates: Structural equation modeling (SEM). Kasetsart Journal of Social Sciences, 43(1), 223–230. https://doi.org/10.34044/j.kjss.2022.43.1.30
12.
ChoiN.FuquaD. R.GriffinB. W. (2001). Exploratory analysis of the structure of scores from the multidimensional scales of perceived self-efficacy. Educational and Psychological Measurement, 61(3), 475–489. https://doi.org/10.1177/00131640121971338
13.
ClearyT. J.KitsantasA. (2017). Motivation and self-regulated learning influences on middle school mathematics achievement. School Psychology Review, 46(1), 88–107. https://doi.org/10.1080/02796015.2017.12087607
CooperH.HedgesL. V.ValentineJ. C. (2019). The handbook of research synthesis and meta-analysis. Russell Sage Foundation.
16.
CortinaJ. M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98–104. https://doi.org/10.1037/0021-9010.78.1.98
17.
CrockerL.AlginaJ. (1986). Introduction to classical and modern test theory. Harcourt.
18.
CruchinhoP.López-FrancoM. D.CapelasM. L.BennettP. M.Miranda da SilvaM.TeixeiraG.NunesE.LucasP.GasparF.Handovers4SafeCare. (2024). Translation, cross-cultural adaptation, and validation of measurement instruments: A practical guideline for novice researchers. Journal of Multidisciplinary Healthcare, 17, 2701–2728. https://doi.org/10.2147/JMDH.S419714
19.
CuiY. (2021). Self-efficacy for self-regulated learning and Chinese students’ intention to use online learning in covid-19: A moderated mediation model. International Journal of Information and Education Technology, 11(11), 532–537. https://doi.org/10.18178/ijiet.2021.11.11.1561
20.
DuganR.AndradeH. (2011). Exploring the construct validity of academic self-regulation using a new self report questionnaire – The survey of academic self-regulation. The International Journal of Educational and Psychological Assessment, 7(1), 45–63. https://scholarsarchive.library.albany.edu/edpsych_fac_scholar/1
21.
DuvalS.TweedieR. (2000). Trim and fill: A simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56(2), 455–463. https://doi.org/10.1111/j.0006341X.2000.00455.x
22.
EggerM.SmithG. D.SchneiderM.MinderC. (1997). Bias in meta-analysis detected by a simple, graphical test. British Medical Journal, 315(7109), 629–634. https://doi.org/10.1136/bmj.315.7109.629
23.
EllisJ. M.HelaireL. J. (2018). The effects of adolescent self-regulated learning on engagement in a college access program: An exploratory study. AERA Open, 4(1), 1–17. https://doi.org/10.1177/2332858418756051
24.
Gisbert-PérezJ.Martí-VilarM.Merino-SotoC.Vallejos-FloresM. (2022). Reliability generalization meta-analysis of internet gaming disorder scale. Healthcare, 10(10), 1992. https://doi.org/10.3390/healthcare10101992
25.
GnambsT. (2015). Sociodemographic effects on the test–retest reliability of the big five inventory. European Journal of Psychological Assessment, 31(4), 258–263. https://doi.org/10.1027/1015-5759/a000259
26.
GocenS.SenS. (2025). Reliability generalization meta-analysis of nine mathematics anxiety scales. Current Psychology, 44(11), 10521–10533. https://doi.org/10.1007/s12144-025-07877-x
27.
GreenS. B.YangY. (2015). Evaluation of dimensionality in the assessment of internal consistency reliability: Coefficient alpha and omega coefficients. Educational Measurement: Issues and Practice, 34(4), 14–20. https://doi.org/10.1111/emip.12100
28.
Hidalgo-FuentesS. (2023). Smartphone application-based addiction scale: A reliability generalization Meta analysis. European Journal of Education and Psychology, 16(1), 1–20. https://doi.org/10.32457/ejep.v16i1.1954
HemmlerY. M.IfenthalerD. (2024). Self-regulated learning strategies in continuing education: A systematic review and meta-analysis. Educational Research Review, 45,Article 100629. https://doi.org/10.1016/j.edurev.2024.100629
31.
HensonR. K.KoganL. R.Vacha-HaaseT. (2001). A reliability generalization study of the teacher efficacy scale and related instruments. Educational and Psychological Measurement, 61(3), 404–420. https://doi.org/10.1177/00131640121971284
32.
HigginsJ. P.ThompsonS. G. (2002). Quantifying heterogeneity in a meta-analysis. Statistics in Medicine, 21(11), 1539–1558. https://doi.org/10.1002/sim.1186
33.
HigginsJ. P.ThompsonS. G.DeeksJ. J.AltmanD. G. (2003). Measuring inconsistency in meta analyses. BMJ, 327(7414), 557–560. https://doi.org/10.1136/bmj.327.7414.557
34.
Huedo-MedinaT.Sanchez-MecaJ.Marin-MartinezF.BotellaJ. (2006). Assessing heterogeneity in meta analysis: Q statistic or I2 index?Psychological Methods, 11(2), 193–206. https://doi.org/10.1037/1082989X.11.2.193
35.
HusainW.HaddadA. J.HusainM. A.KhanR.TrabelsiK.AmmarA.SaifZ.PakpourA.JahramiH. (2025). Reliability generalization meta-analysis of the internal consistency of the big five inventory (BFI) by comparing BFI (44 items) and BFI-2 (60 items) versions controlling for age, sex, language factors. BMC Psychology, 13(1), 20. https://doi.org/10.1186/s40359-024-02271-x
KimD. H.WangC.AhnH. S.BongM. (2015). English language learners’ self-efficacy profiles and relationship with self-regulated learning strategies. Learning and Individual Differences, 38, 136–142. https://doi.org/10.1016/j.lindif.2015.01.016
38.
KimY. E.YuS. L.ShinJ. (2022). How temptation changes across time: Effects of self-efficacy for self-regulated learning and autonomy support. Educational Psychology, 42(3), 278–295. https://doi.org/10.1080/01443410.2021.2009774
39.
KlassenR. M. (2010). Confidence to manage learning: The self-efficacy for self-regulated learning of early adolescents with learning disabilities. Learning Disability Quarterly, 33(1), 19–30. https://doi.org/10.1177/073194871003300102
40.
KlineR. B. (2009). Measurement. In KlineR. B. (Ed.), Becoming a behavioral science researcher: A guide to producing research that matters (pp. 191–222). Guilford Press.
41.
KnappG.HartungJ. (2003). Improved tests for a random effects meta-regression with a single covariate. Statistics in Medicine, 22(17), 2693–2710. https://doi.org/10.1002/sim.1482
42.
KonstantopoulosS.HedgesL. V. (2019). Statistically analyzing effect sizes: Fixed-and random-effects models. In CooperH.HedgesL. V.ValentineJ. C. (Eds.), The handbook of research synthesis and meta-analysis (3rd ed., pp. 245–279). Russell Sage Foundation.
43.
LanganD.HigginsJ. P. T.JacksonD.BowdenJ.VeronikiA. A.KontopantelisE.ViechtbauerW.SimmondsM. (2019). A comparison of heterogeneity variance estimators in simulated random-effects meta-analyses. Research Synthesis Methods, 10(1), 83–98. https://doi.org/10.1002/jrsm.1316
44.
LazićM.JovanovićV.Gavrilov-JerkovićV. (2021). The general self-efficacy scale: New evidence of structural validity, measurement invariance, and predictive properties in relationship to subjective well being in Serbian samples. Current Psychology, 40(2), 699–710. https://doi.org/10.1007/s12144-018-9992-6
45.
LeeJ.PaekI. (2014). In search of the optimal number of response categories in a rating scale. Journal of Psychoeducational Assessment, 32(7), 663–673. https://doi.org/10.1177/0734282914522200
46.
LeppA.BarkleyJ. E.KarpinskiA. C. (2015). The relationship between cell phone use and academic performance in a sample of US college students. Sage Open, 5(1), 1–9. https://doi.org/10.1177/2158244015573169
47.
López-IbáñezC.López-NicolásR.Blázquez-RincónD. M.Sánchez-MecaJ. (2024). Reliability generalization meta-analysis: Comparing different statistical methods. Current Psychology, 43, 18275–18293. https://doi.org/10.1007/s12144-023-05604-y
48.
López-PinaJ. A.Sánchez-MecaJ.López-LópezJ. A.Marín-MartínezF.Núñez-NúñezvR. M.Rosa AlcázarFerrer-RequenaA. I. J. (2015). The yale–brown obsessive compulsive scale: A reliability generalization meta-analysis. Assessment, 22(5), 619–628. https://doi.org/10.1177/1073191114551954
49.
McNeishD. (2018). Thanks coefficient alpha, we’ll take it from here. Psychological Methods, 23(3), 412–433. https://doi.org/10.1037/met0000144
MoherD.LiberatiA.TetzlaffJ.AltmanD. G.PRISMA Group. (2010). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. International Journal of Surgery, 8(5), 336–341. https://doi.org/10.1016/j.ijsu.2010.02.007
52.
MorelliM.ChirumboloA.BaioccoR.CattelinoE. (2023). Self-regulated learning self efficacy, motivation, and intention to drop-out: The moderating role of friendships at university. Current Psychology, 42(18), 15589–15599. https://doi.org/10.1007/s12144-022-02834-4
53.
MuñizJ.Garcı́a-CuetoE.LozanoL. M. (2005). Item format and the psychometric properties of the eysenck personality questionnaire. Personality and Individual Differences, 38(1), 61–69. https://doi.org/10.1016/j.paid.2004.03.021
54.
NunnallyJ. C.BernsteinI. H. (1994). Psychometric theory. McGraw-Hill.
55.
OrhanA. (2024). Trait emotional intelligence questionnaire short form (teique-sf): Reliability generalization meta-analysis.Personality and Individual Differences, 224, Article 112633. https://doi.org/10.1016/j.paid.2024.112633
56.
PaezA. (2017). Gray literature: An important resource in systematic reviews. Journal of Evidence-Based Medicine, 10(3), 233–240. https://doi.org/10.1111/jebm.12266
PajaresF.ValianteG. (2001). Gender differences in writing motivation and achievement of middle school students: A function of gender orientation?Contemporary Educational Psychology, 26(3), 366–381. https://doi.org/10.1006/ceps.2000.1069
59.
PanaderoE. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 28(8), 422. https://doi.org/10.3389/fpsyg.2017.00422
60.
PanaderoE.TapiaJ. A.HuertasJ. A. (2012). Rubrics and self-assessment scripts effects on self-regulation, learning and self-efficacy in secondary education. Learning and Individual Differences, 22(6), 806–813. https://doi.org/10.1016/j.lindif.2012.04.007
61.
PastorelliC.CapraraG. V.BarbaranelliC.RolaJ.RozsaS.BanduraA. (2001). The structure of children's perceived self-efficacy: A cross-national study. European Journal of Psychological Assessment, 17(2), 87. https://doi.org/10.1027/10155759.17.2.87
62.
PintrichP. R.SmithD. A. F.GarcíaT.McKeachieW. J. (1991). A manual for the use of the motivated strategies for learning questionnaire (MSLQ). University of Michigan, National Center for Re-search to Improve Postsecondary Teaching and Learning.
63.
RaykovT. (2001). Bias of coefficient alpha for fixed congeneric measures with correlated errors. Applied Psychological Measurement, 25(1), 69–76. https://doi.org/10.1177/01466216010251005
64.
RaykovT.MarcoulidesG. A. (2016). Scale reliability evaluation under multiple assumption violations. Structural Equation Modeling: A Multidisciplinary Journal, 23(2), 302–313. https://doi.org/10.1080/10705511.2014.938597
65.
R Core Team. (2022). R: A language and environment for statistical computing. [Computer software]. https://cran.r-project.org
66.
ReiseS. P.BonifayW. E.HavilandM. G. (2012). Scoring and modeling psychological measures in the presence of multidimensionality. Journal of Personality Assessment, 95(2), 129–140. https://doi.org/10.1080/00223891.2012.725437
67.
RothA.OgrinS.SchmitzB. (2016). Assessing self-regulated learning in higher education: A systematic literature review of self-report instruments. Educational Assessment, Evaluation and Accountability, 28(3), 225–250. https://doi.org/10.1007/s11092-015-9229-2
68.
RothsteinH. R. (2008). Publication bias as a threat to the validity of meta-analytic results. Journal of Experimental Criminology, 4(1), 61–81. https://doi.org/10.1007/s11292-007-9046-9
69.
RovanD.PetričevićE.Pavlin-BernardićN. (2024). The role of motivational beliefs in the self-regulated learning of mathematics: The reconceptualization of the expectancy value framework. European Journal of Psychology of Education, 39(2), 1205–1227. https://doi.org/10.1007/s10212023-00733-1
70.
Sánchez-MecaJ.Lopez-LopezJ. A.Lopez-PinaJ. A. (2013). Some recommended statistical analytic practices when reliability generalization studies are conducted. British Journal of Mathematical and Statistical Psychology, 66(3), 402–425. https://doi.org/10.1111/j.2044-8317.2012.02057.x
71.
Sánchez‐MecaJ.Marín‐MartínezF.López‐LópezJ. A.Núñez‐NúñezR. M.Rubio AparicioM.López GarcíaLópez‐NicolásJ. J. R. (2021). Improving the reporting quality of reliability generalization meta‐analyses: The REGEMA checklist. Research Synthesis Methods, 12(4), 516–536. https://doi.org/10.1002/jrsm.1487
SenS. (2022). A reliability generalization meta-analysis of runco ideational behavior scale. Creativity Research Journal, 34(2), 178–194. https://doi.org/10.1080/10400419.2021.1960719
74.
SenS.YörükS. (2024) (Submitted for publication). Adaptation of the Runco Ideational Behavior Scale into Turkish: A confirmatory factor analysis and Rasch study.Psychology of Aesthetics, Creativity, and the Arts.https://doi.org/10.1037/aca0000676
75.
SijtsmaK. (2009). On the use, the misuse, and the very limited usefulness of Cronbach’s alpha. Psychometrika, 74(1), 107–120. https://doi.org/10.1007/s11336-008-9101-0
76.
SutherlandK.BrockG.e Villiers ScheepersM.J.MillearP.M., et al. (2023). Non-traditional students’ preferences for learning technologies and impacts on academic self-efficacy. J Comput High Educ, 36, 298–319. https://doi.org/10.1007/s12528-023-09354-5
77.
TavakolM.DennickR. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53–55. https://doi.org/10.5116/ijme.4dfb.8dfd
78.
TengL. S.ZhangL. J. (2018). Effects of motivational regulation strategies on writing performance: A mediation model of self-regulated learning of writing in English as a second/foreign language. Metacognition and Learning, 13(2), 213–240. https://doi.org/10.1007/s11409-017-9171-4
79.
UsherE. L.PajaresF. (2008). Self-efficacy for self-regulated learning: A validation study. Educational and Psychological Measurement, 68(3), 443–463. https://doi.org/10.1177/0013164407308475
80.
UsherE. L.PajaresF. (2009). Sources of self-efficacy in mathematics: A validation study. Contemporary Educational Psychology, 34(1), 89–101. https://doi.org/10.1016/j.cedpsych.2008.09.002
81.
Vacha-HaaseT. (1998). Reliability generalization: Exploring variance in measurement error affecting score reliability across studies. Educational and Psychological Measurement, 58(1), 6–20. https://doi.org/10.1177/0013164498058001002
82.
Vacha-HaaseT.HensonR. K.CarusoJ. C. (2002). Reliability generalization: Moving toward improved understanding and use of score reliability. Educational and Psychological Measurement, 62(4), 562–569. https://doi.org/10.1177/0013164402062004002
83.
ViechtbauerW. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1–48. https://doi.org/10.18637/jss.v036.i03
84.
VillaresE.ColvinK.CareyJ.WebbL.BrigmanG.HarringtonK. (2014). Convergent and Divergent Validity of the Student Engagement in School Success Skills Survey. Professional Counselor, 4(5), 541–552.
85.
WeinsteinC. E.PalmerD. R.SchulteA. C. (1987). LASSI: Learning and study strategies inventory. H & H.
86.
WigfieldA.EcclesJ. S. (2000). Expectancy-value theory of achievement motivation. Contemporary Educational Psychology, 25(1), 68–81. https://doi.org/10.1006/ceps.1999.1015
87.
WilkinsonL.Task Force on Statistical InferenceAmerican Psychological AssociationScienceDirectorate. (1999). Statistical methods in psychology journals: Guidelines and explanations. American Psychologist, 54(8), 594–604. https://doi.org/10.1037/0003-066X.54.8.594
88.
XuZ.ZhaoY.ZhangB.LiewJ.KogutA. (2023). A meta-analysis of the efficacy of self-regulated learning interventions on academic achievement in online and blended environments in K-12 and higher education. Behaviour & Information Technology, 42(16), 2911–2931. https://doi.org/10.1080/0144929X.2022.2151935
89.
ZafarM. B.Abu-HussinM. F. (2024). Reliability generalization meta-analysis of measuring Islamic work ethic. Current Psychology, 43(42), 1–13. https://doi.org/10.1007/s12144-024-06835-3
90.
ZimmermanB. J. (2000). Attaining self-regulation: A social cognitive perspective. In BoekaertsM.PintrichP. R.ZeidnerM. (Eds.), Handbook of self-regulation (pp. 13–39). Academic Press. https://doi.org/10.1016/B978-012109890-2/50031-7
91.
ZimmermanB. J. (2001). Achieving academic excellence: A self-regulatory perspective. In FerrariM. (Ed.), The pursuit of excellence through education (pp. 85–110). Routledge.
92.
ZimmermanB. J.BanduraA.Martinez-PonsM. (1992). Self-motivation for academic attainment: The role of self-efficacy beliefs and personal goal setting. American Educational Research Journal, 29(3), 663-676. https://doi.org/10.3102/00028312029003663
93.
ZimmermanB. J.ClearyT. J. (2006). Adolescents’ development of personal agency: The role of self-efficacy beliefs and self-regulatory skill. In PajaresF.UrdanT. C. (Eds.), Self-efficacy beliefs of adolescents: A volume in adolescence and education (pp. 45–69). Information Age.
94.
ZimmermanB. J.Martinez-PonsM. (1986). Development of a structured interview for assessing student use of self-regulated learning strategies. American Educational Research Journal, 23(4), 614–628. https://doi.org/10.3102/000283120230046
95.
ZuffianòA.AlessandriG.GerbinoM.KanacriB. P. L.Di GiuntaL.MilioniM.CapraraG. V. (2013). Academic achievement: The unique contribution of self-efficacy beliefs in self-regulated learning beyond intelligence, personality traits, and self-esteem. Learning and Individual Differences, 23, 158–162. https://doi.org/10.1016/j.lindif.2012.07.010
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