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Classroom Attendance Scale Development and Validation Study

Year 2022, Issue: 35, 235 - 242, 07.05.2022

Adem Akkuş

https://doi.org/10.31590/ejosat.1063599

Abstract

Classroom Attendance Scale (CAS) is prepared with 14 items. Prepared CAS consists of items with likert type. Sample of the study consists of 318 college students who study at education faculty at science education and primary education programs along with students who work at engineering faculty. Principal axis factoring with orthogonal rotation (varimax) is used for exploratory factor analysis. Factor eigenvalues are obtained and corrected-item total correlations were analyzed. Items which did not serve the purpose of scale were omitted from CAS. Thus, analyses with same procedure were reconducted several times until reaching to a final version of the CAS. A confirmatory factor analysis with Maximum Likelihood is applied to a different sample (N=229) and CAS is approved by most common fit indices values. Total sample of the study consists of 547 participants and finalized CAS consists of 8 items and scale’s Cronbach’s alpha value is .923

Keywords

attendance classroom attendance classroom attitude scale development

References

  • Ajzen, I. (2005a). Behavioral interventions based on the theory of planned behavior: Brief description of the theory of planned behavior. http://people.umass.edu/aizen/pdf/tpb.intervention.pdf
  • Ajzen, I. (2005b). Constructing a theory of planned behavior questionnaire: Brief description of the theory of planned behavior. http://people.umass.edu/aizen/pdf/tpb.measurement.pdf
  • Ajzen, I. (2005c). Sample TpB questionnare. http://people.umass.edu/aizen/pdf/tpb.questionnaire.pdf
  • Akkus, A. (2013). Informing Science and Technology Teachers About Cooperative Learning Model, Application of the Model in the Classroom and Evaluation of the Obtained Data: Case of MUŞ. Unpublished Doctorate Thesis, Ataturk University, Turkey.
  • Amoo, A. O., & Swart, A. J. (2018, 17-20 April). The influence of class attendance on the throughput rates of students at a FET college in South Africa [Paper presentation]. IEEE Global Engineering Education Conference: EDUCON, Tenerife, Spain. https://doi.org/10.1109/EDUCON.2018.8363101
  • Anthoine, E., Moret, L., Regnault, A., Sébille, V., & Hardouin, J.-B. (2014). Sample size used to validate a scale: a review of publications on newly-developed patient reported outcomes measures. Health and Quality of Life Outcomes, 12, 2. http://doi.org/10.1186/s12955-014-0176-2
  • Brinkman, W-P. (2009). Design of a questionnaire instrument, handbook of mobile technology research methods (pp. 31-57). Nova Publisher
  • Cabrera-Nguyen, P. (2010). Author guidelines for reporting scale development and validation results in the Journal of the Society for Social Work and Research. Journal of the Society for Social Work and Research, 1 (2), 99-103.
  • Chen, J., & Lin, T.-F. (2008). Class Attendance and Exam Performance: A Randomized Experiment. The Journal of Economic Education, 39 (3), 213–227. http://doi.org/10.3200/jece.39.3.213-227
  • Chen, S. (2006). Development of a instrument to assess views on nature of science and attitudes toward teaching science. Science Education, 90 (5), 803-819. http://doi.org/10.1002/sce.20147
  • Clark, L.A. & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7 (3), 309-319.
  • Cohn, E. & Johnson, E. (2006) Class attendance and performance in principles of economics. Education Economics, 14 (2), 211-233. http://doi.org/10.1080/09645290600622954
  • Crede, M., Roch, S. G., & Kieszczynka, U. M. (2010). Class Attendance in College: A meta-analytic review of the relationship of class attendance with grades and student characteristics. Review of Educational Research, 80 (2), 272–295. http://doi.org/10.3102/0034654310362998
  • Demirutku, K. & Tekinay, S. (2016). The relationships between human values, absenteeism attitudes and reasons. Hacettepe University Journal of Education, 31 (3), 505-519. http://doi.org/10.16986/HUJE.2016016667
  • Deshpande, L. (2004, December 13-17). Challenges in measurement of scientific attitude [Paper presentation]. epiSTEME-1: An International Conference to Review Research on Science Technology And Mathematics Education, Goa, India.
  • Devadoss, S., & Foltz, J. (1996). Evaluation of Factors Influencing Student Class Attendance and Performance. American Journal of Agricultural Economics, 78 (3), 499–507. http://doi.org/10.2307/1243268
  • Durden, G.C. & Ellis, L.V. (1995). The effects of attendance on student learning in principles of economics. The American Economic Review, 85 (2), 343-346
  • Eryılmaz., A. (2014). The Development of the Scales of Classroom Engagement for University Students. Usak university of Journal of Social Sciences, 7 (2), 203-214
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th Edition). SAGE
  • Francis, J., Eccles, M. P., Johnston, M., Walker, A. E., Grimshaw, J. M., Foy, R., Kaner, E. F. S., Smith, L. and Bonetti, D. (2004). Constructing questionnaires based on the theory of planned behaviour: A manual for health services researchers. UK: Centre for Health Services Research, University of Newcastle upon Tyne
  • Fjortoft,N. (2005). Students’ motivations for class attendance. American Journal of Pharmaceutical Education, 69 (1), 107-112.
  • Friedman, P., Rodriguez, F., & McComb, J. (2001). Why Students Do and Do Not Attend Classes. College Teaching, 49 (4), 124–133. http://doi.org/10.1080/87567555.2001.10844593
  • Gump, S. E. (2005). The Cost of Cutting Class: Attendance As A Predictor of Success. College Teaching, 53 (1), 21–26. http://doi.org/10.3200/ctch.53.1.21-26
  • Hemyari, C., Zomorodian, K., Sahraian, A., Mardani, Z., Sarkari, B. & Ahmadi, N. (2017). Impact of students’ class attendance on recalling previously acquired information. Journal of Medical Education, 16 (4), 208-214.
  • Hilal Bati, A., Mandiracioglu, A., Orgun, F. & Govsa, F. (2013). Why do students miss lectures? A study of lecture attendance amongst students of health science. Nurse Education Today, 33, 596-601. http://doi.org/10.1016/j.nedt.2012.07.010
  • Hinkin, T. R. (1998). A brief tutorial on the development of measures for use in survey questionnaires. Organizational Research Methods, 2 (1), 104-121 http://doi.org/10.1177/109442819800100106
  • Hinkin, T. R., Tracey, J. B., & Enz, C. A. (1997). Scale construction: Developing reliable and valid measurement instruments. Journal of Hospitality & Tourism Research, 21 (1), 100-120. http://doi.org/10.1177/109634809702100108
  • Hof, M.W. (2012). Questionnaire Evaluation with Factor Analysis and Cronbach ’ s Alpha : An Example. http://www.let.rug.nl/nerbonne/teach/rema-stats-meth-seminar/student-papers/MHof-QuestionnaireEvaluation-2012-Cronbach-FactAnalysis.pdf
  • Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modeling: Guidelines for determining model fit. Journal of Business Research Methods, 6(1), 53–60. http://www.ejbrm.com/issue/download.html?idArticle=183
  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. http://doi.org/10.1080/10705519909540118
  • Jha, K., Kumar, Y., Kumar, T. & Singh, R. (2017). Does stressor and class attendance affect academic performance of medical students? A cross sectional study. Global Journal for Research Analysis, 6 (11), 373-375.
  • Johanson, G.A., & Brooks, G.P. (2010). Initial scale development: Sample size for pilot studies. Educational and Psychological Measurement, 70 (3), 394-400. http://doi.org/10.1177/0013164409355692
  • Johnson, R.L. & Morgan, G.B. (2016). Survey scales: Investigating scale quality. The Guilford Press.
  • Kalaycı, Ş. (2010). SPSS uygulamalı çok değişkenli istatistik teknikleri. (5. Baskı) [SPSS applications multivariate statistical techniques (5th edition)]. Asil Yayın Dağıtım Ltd. Şti.
  • Lovelace, M. and Brickman, P. (2013). Best practices for measuring students’ attitudes toward learning science. CBE-Life Sciences Education, 12 (4), 606-617. http://doi.org/10.1187/cbe.12-11-0197
  • Madans, J. H. (2001). Health Surveys. International Encyclopedia of the Social & Behavioral Sciences, 6619–6627. http://doi.org/10.1016/b0-08-043076-7/03903-6
  • Madden, T. J., Ellen, P. S., & Ajzen, I. (1992). A Comparison of the Theory of Planned Behavior and the Theory of Reasoned Action. Personality and Social Psychology Bulletin, 18 (1), 3–9. http://doi.org/10.1177/0146167292181001
  • Moore, R.W. & Foy, R.L.H. (1997). The scientific attitude inventory: A revision (SAI II). Journal of Research in Science Teaching, 34 (4), 327-336.
  • Pryor, B. W. (1990). Predicting and Explaining Intentions to Participate in Continuing Education: An Application of the Theory of Reasoned Action. Adult Education Quarterly, 40 (3), 146–157. http://doi.org/10.1177/0001848190040003003
  • Teo, T. & Lee, C. B. (2010). Examining the efficacy of the Theory of Planned Behavior (TPB) to understand pre-service teachers’ intention to use technology. In C.H. Steel, M.J.
  • Keppell, P. Gerbic & S. Housego (Eds.), Curriculum, technology & transformation for an unknown future. Proceedings ascilite Sydney 2010 (pp.968-972) http://ascilite.org.au/conferences/sydney10/procs/Teo-concise.pdf
  • Senemoglu, N. (2013). Gelişim, öğrenme ve öğretim. Kuramdan uygulamaya [Development, learning and instruction. From theory to application]. Yargı Publications
  • Sümer, N. (2000). Structural equation models: Basic concepts and sample applications. Turkish Psychological Articles, 3 (6), 49–74. https://www.researchgate.net/publication/281981476_Yapidotlesssal_esitlik_modelleri_Temel_kavramlar_ve_ornek_uygulamalar
  • Trafimow, D. (2009). The Theory of Reasoned Action. Theory & Psychology, 19 (4), 501–518. http://doi.org/10.1177/0959354309336319
  • Van Blerkom, M. L. (1992). Class Attendance in Undergraduate Courses. The Journal of Psychology, 126 (5), 487–494. http://doi.org/10.1080/00223980.1992.10543382
  • Watkins, M. W. (2000). Monte carlo PCA for parallel analysis [computer software]. State College, PA: Ed & Psych Associates.
  • Wong., M. & Lian, S. (2003). Development of a self-efficacy scale for assessing secondary school students’ science self-efficacy beliefs. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.472.8479
  • Yıldırım, B., & Selvi, M. (2015). Adaptation of STEM attitude scale to Turkish. Turkish Studies: International Periodical for the Languages, Literature and History of Turkish or Turkic, 10(3), 1117–1130. https://dx.doi.org/10.7827/TurkishStudies.7974

Classroom Attendance Scale Development and Validation Study

Year 2022, Issue: 35, 235 - 242, 07.05.2022

Adem Akkuş

https://doi.org/10.31590/ejosat.1063599

Abstract

Classroom Attendance Scale (CAS) is prepared with 14 items. Prepared CAS consists of items with likert type. Sample of the study consists of 318 college students who study at education faculty at science education and primary education programs along with students who work at engineering faculty. Principal axis factoring with orthogonal rotation (varimax) is used for exploratory factor analysis. Factor eigenvalues are obtained and corrected-item total correlations were analyzed. Items which did not serve the purpose of scale were omitted from CAS. Thus, analyses with same procedure were reconducted several times until reaching to a final version of the CAS. A confirmatory factor analysis with Maximum Likelihood is applied to a different sample (N=229) and CAS is approved by most common fit indices values. Total sample of the study consists of 547 participants and finalized CAS consists of 8 items and scale’s Cronbach’s alpha value is .923

Keywords

attendance classroom attendance classroom attitude scale development

References

  • Ajzen, I. (2005a). Behavioral interventions based on the theory of planned behavior: Brief description of the theory of planned behavior. http://people.umass.edu/aizen/pdf/tpb.intervention.pdf
  • Ajzen, I. (2005b). Constructing a theory of planned behavior questionnaire: Brief description of the theory of planned behavior. http://people.umass.edu/aizen/pdf/tpb.measurement.pdf
  • Ajzen, I. (2005c). Sample TpB questionnare. http://people.umass.edu/aizen/pdf/tpb.questionnaire.pdf
  • Akkus, A. (2013). Informing Science and Technology Teachers About Cooperative Learning Model, Application of the Model in the Classroom and Evaluation of the Obtained Data: Case of MUŞ. Unpublished Doctorate Thesis, Ataturk University, Turkey.
  • Amoo, A. O., & Swart, A. J. (2018, 17-20 April). The influence of class attendance on the throughput rates of students at a FET college in South Africa [Paper presentation]. IEEE Global Engineering Education Conference: EDUCON, Tenerife, Spain. https://doi.org/10.1109/EDUCON.2018.8363101
  • Anthoine, E., Moret, L., Regnault, A., Sébille, V., & Hardouin, J.-B. (2014). Sample size used to validate a scale: a review of publications on newly-developed patient reported outcomes measures. Health and Quality of Life Outcomes, 12, 2. http://doi.org/10.1186/s12955-014-0176-2
  • Brinkman, W-P. (2009). Design of a questionnaire instrument, handbook of mobile technology research methods (pp. 31-57). Nova Publisher
  • Cabrera-Nguyen, P. (2010). Author guidelines for reporting scale development and validation results in the Journal of the Society for Social Work and Research. Journal of the Society for Social Work and Research, 1 (2), 99-103.
  • Chen, J., & Lin, T.-F. (2008). Class Attendance and Exam Performance: A Randomized Experiment. The Journal of Economic Education, 39 (3), 213–227. http://doi.org/10.3200/jece.39.3.213-227
  • Chen, S. (2006). Development of a instrument to assess views on nature of science and attitudes toward teaching science. Science Education, 90 (5), 803-819. http://doi.org/10.1002/sce.20147
  • Clark, L.A. & Watson, D. (1995). Constructing validity: Basic issues in objective scale development. Psychological Assessment, 7 (3), 309-319.
  • Cohn, E. & Johnson, E. (2006) Class attendance and performance in principles of economics. Education Economics, 14 (2), 211-233. http://doi.org/10.1080/09645290600622954
  • Crede, M., Roch, S. G., & Kieszczynka, U. M. (2010). Class Attendance in College: A meta-analytic review of the relationship of class attendance with grades and student characteristics. Review of Educational Research, 80 (2), 272–295. http://doi.org/10.3102/0034654310362998
  • Demirutku, K. & Tekinay, S. (2016). The relationships between human values, absenteeism attitudes and reasons. Hacettepe University Journal of Education, 31 (3), 505-519. http://doi.org/10.16986/HUJE.2016016667
  • Deshpande, L. (2004, December 13-17). Challenges in measurement of scientific attitude [Paper presentation]. epiSTEME-1: An International Conference to Review Research on Science Technology And Mathematics Education, Goa, India.
  • Devadoss, S., & Foltz, J. (1996). Evaluation of Factors Influencing Student Class Attendance and Performance. American Journal of Agricultural Economics, 78 (3), 499–507. http://doi.org/10.2307/1243268
  • Durden, G.C. & Ellis, L.V. (1995). The effects of attendance on student learning in principles of economics. The American Economic Review, 85 (2), 343-346
  • Eryılmaz., A. (2014). The Development of the Scales of Classroom Engagement for University Students. Usak university of Journal of Social Sciences, 7 (2), 203-214
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th Edition). SAGE
  • Francis, J., Eccles, M. P., Johnston, M., Walker, A. E., Grimshaw, J. M., Foy, R., Kaner, E. F. S., Smith, L. and Bonetti, D. (2004). Constructing questionnaires based on the theory of planned behaviour: A manual for health services researchers. UK: Centre for Health Services Research, University of Newcastle upon Tyne
  • Fjortoft,N. (2005). Students’ motivations for class attendance. American Journal of Pharmaceutical Education, 69 (1), 107-112.
  • Friedman, P., Rodriguez, F., & McComb, J. (2001). Why Students Do and Do Not Attend Classes. College Teaching, 49 (4), 124–133. http://doi.org/10.1080/87567555.2001.10844593
  • Gump, S. E. (2005). The Cost of Cutting Class: Attendance As A Predictor of Success. College Teaching, 53 (1), 21–26. http://doi.org/10.3200/ctch.53.1.21-26
  • Hemyari, C., Zomorodian, K., Sahraian, A., Mardani, Z., Sarkari, B. & Ahmadi, N. (2017). Impact of students’ class attendance on recalling previously acquired information. Journal of Medical Education, 16 (4), 208-214.
  • Hilal Bati, A., Mandiracioglu, A., Orgun, F. & Govsa, F. (2013). Why do students miss lectures? A study of lecture attendance amongst students of health science. Nurse Education Today, 33, 596-601. http://doi.org/10.1016/j.nedt.2012.07.010
  • Hinkin, T. R. (1998). A brief tutorial on the development of measures for use in survey questionnaires. Organizational Research Methods, 2 (1), 104-121 http://doi.org/10.1177/109442819800100106
  • Hinkin, T. R., Tracey, J. B., & Enz, C. A. (1997). Scale construction: Developing reliable and valid measurement instruments. Journal of Hospitality & Tourism Research, 21 (1), 100-120. http://doi.org/10.1177/109634809702100108
  • Hof, M.W. (2012). Questionnaire Evaluation with Factor Analysis and Cronbach ’ s Alpha : An Example. http://www.let.rug.nl/nerbonne/teach/rema-stats-meth-seminar/student-papers/MHof-QuestionnaireEvaluation-2012-Cronbach-FactAnalysis.pdf
  • Hooper, D., Coughlan, J., & Mullen, M. R. (2008). Structural equation modeling: Guidelines for determining model fit. Journal of Business Research Methods, 6(1), 53–60. http://www.ejbrm.com/issue/download.html?idArticle=183
  • Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. http://doi.org/10.1080/10705519909540118
  • Jha, K., Kumar, Y., Kumar, T. & Singh, R. (2017). Does stressor and class attendance affect academic performance of medical students? A cross sectional study. Global Journal for Research Analysis, 6 (11), 373-375.
  • Johanson, G.A., & Brooks, G.P. (2010). Initial scale development: Sample size for pilot studies. Educational and Psychological Measurement, 70 (3), 394-400. http://doi.org/10.1177/0013164409355692
  • Johnson, R.L. & Morgan, G.B. (2016). Survey scales: Investigating scale quality. The Guilford Press.
  • Kalaycı, Ş. (2010). SPSS uygulamalı çok değişkenli istatistik teknikleri. (5. Baskı) [SPSS applications multivariate statistical techniques (5th edition)]. Asil Yayın Dağıtım Ltd. Şti.
  • Lovelace, M. and Brickman, P. (2013). Best practices for measuring students’ attitudes toward learning science. CBE-Life Sciences Education, 12 (4), 606-617. http://doi.org/10.1187/cbe.12-11-0197
  • Madans, J. H. (2001). Health Surveys. International Encyclopedia of the Social & Behavioral Sciences, 6619–6627. http://doi.org/10.1016/b0-08-043076-7/03903-6
  • Madden, T. J., Ellen, P. S., & Ajzen, I. (1992). A Comparison of the Theory of Planned Behavior and the Theory of Reasoned Action. Personality and Social Psychology Bulletin, 18 (1), 3–9. http://doi.org/10.1177/0146167292181001
  • Moore, R.W. & Foy, R.L.H. (1997). The scientific attitude inventory: A revision (SAI II). Journal of Research in Science Teaching, 34 (4), 327-336.
  • Pryor, B. W. (1990). Predicting and Explaining Intentions to Participate in Continuing Education: An Application of the Theory of Reasoned Action. Adult Education Quarterly, 40 (3), 146–157. http://doi.org/10.1177/0001848190040003003
  • Teo, T. & Lee, C. B. (2010). Examining the efficacy of the Theory of Planned Behavior (TPB) to understand pre-service teachers’ intention to use technology. In C.H. Steel, M.J.
  • Keppell, P. Gerbic & S. Housego (Eds.), Curriculum, technology & transformation for an unknown future. Proceedings ascilite Sydney 2010 (pp.968-972) http://ascilite.org.au/conferences/sydney10/procs/Teo-concise.pdf
  • Senemoglu, N. (2013). Gelişim, öğrenme ve öğretim. Kuramdan uygulamaya [Development, learning and instruction. From theory to application]. Yargı Publications
  • Sümer, N. (2000). Structural equation models: Basic concepts and sample applications. Turkish Psychological Articles, 3 (6), 49–74. https://www.researchgate.net/publication/281981476_Yapidotlesssal_esitlik_modelleri_Temel_kavramlar_ve_ornek_uygulamalar
  • Trafimow, D. (2009). The Theory of Reasoned Action. Theory & Psychology, 19 (4), 501–518. http://doi.org/10.1177/0959354309336319
  • Van Blerkom, M. L. (1992). Class Attendance in Undergraduate Courses. The Journal of Psychology, 126 (5), 487–494. http://doi.org/10.1080/00223980.1992.10543382
  • Watkins, M. W. (2000). Monte carlo PCA for parallel analysis [computer software]. State College, PA: Ed & Psych Associates.
  • Wong., M. & Lian, S. (2003). Development of a self-efficacy scale for assessing secondary school students’ science self-efficacy beliefs. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.472.8479
  • Yıldırım, B., & Selvi, M. (2015). Adaptation of STEM attitude scale to Turkish. Turkish Studies: International Periodical for the Languages, Literature and History of Turkish or Turkic, 10(3), 1117–1130. https://dx.doi.org/10.7827/TurkishStudies.7974
There are 48 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Adem Akkuş 0000-0001-9570-3582

Publication Date May 7, 2022
Published in Issue Year 2022 Issue: 35

Cite

APA Akkuş, A. (2022). Classroom Attendance Scale Development and Validation Study. Avrupa Bilim Ve Teknoloji Dergisi(35), 235-242. https://doi.org/10.31590/ejosat.1063599
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