The Effectiveness of Blended and Printed Learning Resources in Improving Science Learning Outcomes of Student Teachers at a Distance University
DOI:
https://doi.org/10.14738/assrj.79.9024Keywords:
distance education, learning outcomes, blended learning, printed learning resourcesAbstract
Learning resources are an essential factor that determines learning outcomes, especially elementary school teacher education program students in distance education. This study aims to compare the effectiveness of blended learning and printed learning resources in improving science learning outcomes for distance education students. This study is a true experiment conducted at the Universitas Terbuka (UT) regional office of Jember, as a representation of the East Java region. Respondents of the study were 56 students using blended learning resources and 60 students using printed learning resources. The data were collected using a test of student learning outcomes and analyzed using t-test and N-gain. The results show that both blended learning and printed learning resources significantly improved learning outcomes at α = 5%, each with an average N-gain having relatively the same products at moderate levels. This study also raises information that blended learning resources are more effective than printed learning resources. This study implies that blended learning resources can be used as an innovative solution to improve student learning outcomes in distance education systems.
References
Allen, J. E., Seaman, J., & Garret, R. (2007). Blending in - the extent and promise of blended education in the United States. Retrieved from Online Learning Consortium: https://secure.online learningconsortium.org/publications/ survey/blended06.
Ashoori, J., Kajbaf, M. B., Manshaee, G. R., & Talebi, H. (2020). Comparison of the effectiveness of web-based, cooperative learning and traditional teaching methods in achievement motivation and academic achievement in the biology course. Interdisciplinary Journal of Virtual Learning in Medical Sciences, 5(2), 25-34.
Belawati, T. (2005). The impact of online tutorials on course completion rates and student achievement. Learning, Media and Technology, 30(1), 15-25.
Boyd, P., & Ash, A. (2018). Teachers framing exploratory learning within a text-book based Singapore Maths mastery approach. Teacher Education Advancement Network Journal, 10(1), 62-73.
Broadbent, J. (2017). Comparing online and blended learner's self-regulated learning strategies and academic performance. The Internet and Higher Education, 33(1), 24-32.
Brunyé, T. T., Mahoney, C. R., Giles, G. E., Rapp, D. N., Taylor, H. A., & Kanarek, R. B. (2013). Learning to relax: Evaluating four brief interventions for overcoming the negative emotions accompanying math anxiety. Learning and Individual Differences, 27(3), 1-7.
Budiastra, A. K., Erlina, N., & Wicaksono, I. (2019). The factors affecting teachers’ readiness in developing science concept assessment through inquiry-based learning process in elementary schools. Advances in Social Sciences Research Journal, 6(9), 355-366.
Budiastra, A.A. K, Kosasih, F. R and Wicaksono, I. (2019). The new generation of science learning in elementary school course materials development: A lesson from a southeast Asian country. International Journal of Recent Scientific Research, 10(10), 35208-35215.
Budiastra, A. K., Warsihna, J., Widiasih & Puspitasari, S. (2020). The Development of Science Learning Model for Higher Education of Bachelor Elementary School Teacher Education Program in Distance Learning. Advances in Social Sciences Research Journal, 7(5), 54-69.
Callahan, C. M., Azano, A. P., Park, S., Brodersen, A. V., Caughey, M., Bass, E. L., & Amspaugh, C. M. (2020). Validation of instruments for measuring affective outcomes in gifted education. Journal of Advanced Academics, 31(4), 470-505.
Chen, W., Yong, A., & Yao, T. (2016). An empirical evaluation of critical factors influencing learner satisfaction in blended learning: A pilot study. Universal Journal of Educational Research , 4(7), 1667-1671.
Cooper, J., Olsher, S., & Yerushalmy, M. (2020). Didactic metadata informing teachers’ selection of learning resources: Boundary crossing in professional development. Journal of Mathematics Teacher Education, 23(4), 363-384.
Delen, İ., Aktuğ, S., & Helvacı, M. A. (2020). The Need for Contextualized STEM Learning Environments for Refugee Students in Turkey. In International Perspectives on the Contextualization of Science Education (pp. 95-112). Springer, Cham.
Dobrzański, L. A., & Brom, F. (2008). E-learning on the example of materials science. Journal of Achievements in Materials and Manufacturing Engineering, 29(1), 99-102.
Donald, J. G. (2002). Learning to think: disciplinary perspectives. The Jossey-Bass Higher and Adult Education Series. Jossey-Bass, Inc., 989 Market St., San Francisco, CA 94103.
Fatawi, I., Degeng, I. N. S., Setyosari, P., Ulfa, S., & Hirashima, T. (2020). Effect of online-based concept map on student engagement and learning outcome. International Journal of Distance Education Technologies (IJDET), 18(3), 42-56.
Firat, M., & Bozkurt, A. (2020). Variables affecting online learning readiness in an open and distance learning university. Educational Media International, 1-16.
Ghadirian, H., Salehi, K., & Ayub, A. F. M. (2018). Exploring the behavioural patterns of knowledge dimensions and cognitive processes in peer-moderated asynchronous online discussions. International Journal of E-Learning & Distance Education, 33(1), 1-28.
Gusmaneli. (2012). Impact of educational technology against teacher role in the future. Al-Ta'lim Journal, 1(2), 166-172.
Han, F., & Ellis, R. A. (2019). Identifying consistent patterns of quality learning discussions in blended learning. The Internet and Higher Education, 40(4), 12-19.
Hake, R. R. (1998). Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. American journal of Physics, 66(1), 64-74.
Halverson, L. R., & Graham, C. R. (2019). Learner engagement in blended learning environments: A conceptual framework. Online learning, 23(2), 145-178.
Harsasi, M. (2011). Pengembangan computer-assisted instruction sebagai bahan ajar pada Universitas Terbuka [Development of computer-assisted instruction as teaching materials at the Open University]. Konferensi Nasional ICT-M Politeknik Telkom. 92-98.
Held, R. i. (2018). Wissenserwerb mit hypermedialen informationssystemen: von chancen und schwierigkeiten des lernens im internet. Lernen im Internet Münster: Lit Verlag, 13-36.
Herodotou, C., Rienties, B., Hlosta, M., Boroowa, A., Mangafa, C., & Zdrahal, Z. (2020). The scalable implementation of predictive learning analytics at a distance learning university: insights from a longitudinal case study. The Internet and Higher Education, 45-56.
Johnson, S. D., Aragon, S. R., & Shaik, N. (2000). Comparative analysis of learner satisfaction and learning outcomes in online and face-to-face learning environments. Journal of interactive learning research, 11(1), 29-49.
Kayser, I., & Merz, T. (2020). Lone wolves in distance learning?: an empirical analysis of the tendency to communicate within student groups. International Journal of Mobile and Blended learning(IJMBL), 12 (1), 82-94.
Kuznetsov, Y. A. (2013). Elements of applied bifurcation theory (Vol. 112). Springer Science & Business Media.
Lam, J. (2014 ). The context of blended learning: The tips blended learning model. Springer International Publishing, Switzerland, 80-92.
Mustapa, K. (2018). Online instructional strategy with different goals orientation on university students' higher order thinking skills. In First Indonesian Communication Forum of Teacher Training and Education Faculty Leaders International Conference on Education 2017 (ICE 2017). Atlantis Press.
Nguyen, H. T., Duong, P. H., & Cambria, E. (2019). Learning short-text semantic similarity with word embeddings and external knowledge sources. Knowledge-Based Systems, 182, 104842.
Owston, R., York, D. N., & Malhotra, T. (2019). Blended learning in large enrolment courses: Student perceptions across four different instructional models. Australasian Journal of Educational Technology, 35(5), 29-45.
Özyurt, Ö., & Özyurt, H. (2015). Individualized learning style based adaptive e-learning environments: Content analysis of the articles published from 2005 to 2014. Elsevier: Computers in Human Behavior, 52(3), 349-358.
Passwords, G. (2012). Effect of blended learning against chemical judging learning outcomes of students independence. Journal of Education and Teaching, 45(3), 241-251.
Rahmawati, R., Lestari, F., & Umam, R. (2019). Analysis of the effectiveness of learning in the use of learning modules against student learning outcomes. Desimal: Jurnal Matematika, 2(3), 233-240.
Reich, S. M., Subrahmanyam, K., & Espinoza, G. (2012). Friending, iming, and hanging out face-to-face: Overlap in adolescents' online and offline social networks. Developmental Psychology, 48 (2), 356-368.
Serhan, D. (2019). Web-based homework systems: students’ perceptions of course interaction and learning in mathematics. International Journal on Social and Education Sciences, 1(2), 57-62.
Shalihah, F., Supramono, S., & Abdullah, A. (2019). Blended learning-based media usage to practice problem solving skills. European Journal of Education Studies. 17(3), 27-43.
Sharif, I. (2012). Effect of blended learning, model motivation and vocational student achievement. Journal of Vocational Education, 2(2), 234-249.
Skocic Mihic, S., Blanusa Troselj, D., & Katic, V. (2019). Influence of in-service preschool teachers’ education on their perceived competences for counselling parents. CEPS Journal, 9(1), 27-43.
Sugiyono. (2016). Educational Research Methods Quantitative, Qualitative, and R & D Approach. Bandung: Alfabeta.
Sutisna, A. (2016). Learning blended learning and model development on equality education program to enhance independence package e-learning. Journal of Educational Technology, 18(3), 156-168.
Tseng, H., Yi, X., & Yeh, H. T. (2019). Learning-related soft skills among online business students in higher education: Grade level and managerial role differences in self-regulation, motivation, and social skill. Computers in Human Behavior, 95(4), 179-186.
Tytler, R. (2003). A window for a purpose: Developing a framework for describing effective science teaching and learning. Research in Science Education, 33(3), 273-298.
Vo, M. H., Zhu, C., & Diep, A. N. (2020). Examining blended learning implementation in hard and soft sciences: a qualitative analysis. International Journal of Research in Education and Science, 6(2), 250-272.
Walter, C. (2016). What are tutors’ experiences with online teaching?: a phenomenographic study. International Journal of Mobile and Blended learning, 8(1), 18-33.
Wicaksono, I., Madlazim, & Wasis, W. (2017). The effectiveness of virtual science teaching model (VS-TM) to improve student’s scientific creativity and concept mastery on senior high school physics subject. Journal of Baltic Science Education, 16(4), 549-561.
Williams, A. E. (2017). Promoting meaningfulness by coupling Bloom’s taxonomy with adult education theory: introducing an applied and interdisciplinary student writing exercise. Transformative Dialogues: Teaching & Learning Journal, 10(3), 1-11.
Zakirman, Z., Lufri, L., & Khairani, K. (2019). Factors influencing the use of lecture methods in learning activities: Teacher perspective. In 1st International Conference on Innovation in Education (ICoIE 2018). Atlantis Press.
Zorluoglu, S. L., & Güven, Ç. (2020). Analysis of 5th grade science learning outcomes and exam questions according to revised Bloom taxonomy. Journal of Educational Issues, 6(1), 58-69.
Zuhairi, A., Adnan, I., & Thaib, D. (2007). Provision of Student Learning Support Services in a Large-Scale Distance Education System at Universitas Terbuka, Indonesia. Online Submission, 8(4), 44-64.
Zupanc, G. K. (2019). Understanding the role of diffusion in synaptic transmission through inquiry-based learning & quantitative reasoning. The American Biology Teacher, 81(6), 435-441.
Ashoori, J., Kajbaf, M. B., Manshaee, G. R., & Talebi, H. (2020). Comparison of the effectiveness of web-based, cooperative learning and traditional teaching methods in achievement motivation and academic achievement in the biology course. Interdisciplinary Journal of Virtual Learning in Medical Sciences, 5(2), 25-34.
Belawati, T. (2005). The impact of online tutorials on course completion rates and student achievement. Learning, Media and Technology, 30(1), 15-25.
Boyd, P., & Ash, A. (2018). Teachers framing exploratory learning within a text-book based Singapore Maths mastery approach. Teacher Education Advancement Network Journal, 10(1), 62-73.
Broadbent, J. (2017). Comparing online and blended learner's self-regulated learning strategies and academic performance. The Internet and Higher Education, 33(1), 24-32.
Brunyé, T. T., Mahoney, C. R., Giles, G. E., Rapp, D. N., Taylor, H. A., & Kanarek, R. B. (2013). Learning to relax: Evaluating four brief interventions for overcoming the negative emotions accompanying math anxiety. Learning and Individual Differences, 27(3), 1-7.
Budiastra, A. K., Erlina, N., & Wicaksono, I. (2019). The factors affecting teachers’ readiness in developing science concept assessment through inquiry-based learning process in elementary schools. Advances in Social Sciences Research Journal, 6(9), 355-366.
Budiastra, A.A. K, Kosasih, F. R and Wicaksono, I. (2019). The new generation of science learning in elementary school course materials development: A lesson from a southeast Asian country. International Journal of Recent Scientific Research, 10(10), 35208-35215.
Budiastra, A. K., Warsihna, J., Widiasih & Puspitasari, S. (2020). The Development of Science Learning Model for Higher Education of Bachelor Elementary School Teacher Education Program in Distance Learning. Advances in Social Sciences Research Journal, 7(5), 54-69.
Callahan, C. M., Azano, A. P., Park, S., Brodersen, A. V., Caughey, M., Bass, E. L., & Amspaugh, C. M. (2020). Validation of instruments for measuring affective outcomes in gifted education. Journal of Advanced Academics, 31(4), 470-505.
Chen, W., Yong, A., & Yao, T. (2016). An empirical evaluation of critical factors influencing learner satisfaction in blended learning: A pilot study. Universal Journal of Educational Research , 4(7), 1667-1671.
Cooper, J., Olsher, S., & Yerushalmy, M. (2020). Didactic metadata informing teachers’ selection of learning resources: Boundary crossing in professional development. Journal of Mathematics Teacher Education, 23(4), 363-384.
Delen, İ., Aktuğ, S., & Helvacı, M. A. (2020). The Need for Contextualized STEM Learning Environments for Refugee Students in Turkey. In International Perspectives on the Contextualization of Science Education (pp. 95-112). Springer, Cham.
Dobrzański, L. A., & Brom, F. (2008). E-learning on the example of materials science. Journal of Achievements in Materials and Manufacturing Engineering, 29(1), 99-102.
Donald, J. G. (2002). Learning to think: disciplinary perspectives. The Jossey-Bass Higher and Adult Education Series. Jossey-Bass, Inc., 989 Market St., San Francisco, CA 94103.
Fatawi, I., Degeng, I. N. S., Setyosari, P., Ulfa, S., & Hirashima, T. (2020). Effect of online-based concept map on student engagement and learning outcome. International Journal of Distance Education Technologies (IJDET), 18(3), 42-56.
Firat, M., & Bozkurt, A. (2020). Variables affecting online learning readiness in an open and distance learning university. Educational Media International, 1-16.
Ghadirian, H., Salehi, K., & Ayub, A. F. M. (2018). Exploring the behavioural patterns of knowledge dimensions and cognitive processes in peer-moderated asynchronous online discussions. International Journal of E-Learning & Distance Education, 33(1), 1-28.
Gusmaneli. (2012). Impact of educational technology against teacher role in the future. Al-Ta'lim Journal, 1(2), 166-172.
Han, F., & Ellis, R. A. (2019). Identifying consistent patterns of quality learning discussions in blended learning. The Internet and Higher Education, 40(4), 12-19.
Hake, R. R. (1998). Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. American journal of Physics, 66(1), 64-74.
Halverson, L. R., & Graham, C. R. (2019). Learner engagement in blended learning environments: A conceptual framework. Online learning, 23(2), 145-178.
Harsasi, M. (2011). Pengembangan computer-assisted instruction sebagai bahan ajar pada Universitas Terbuka [Development of computer-assisted instruction as teaching materials at the Open University]. Konferensi Nasional ICT-M Politeknik Telkom. 92-98.
Held, R. i. (2018). Wissenserwerb mit hypermedialen informationssystemen: von chancen und schwierigkeiten des lernens im internet. Lernen im Internet Münster: Lit Verlag, 13-36.
Herodotou, C., Rienties, B., Hlosta, M., Boroowa, A., Mangafa, C., & Zdrahal, Z. (2020). The scalable implementation of predictive learning analytics at a distance learning university: insights from a longitudinal case study. The Internet and Higher Education, 45-56.
Johnson, S. D., Aragon, S. R., & Shaik, N. (2000). Comparative analysis of learner satisfaction and learning outcomes in online and face-to-face learning environments. Journal of interactive learning research, 11(1), 29-49.
Kayser, I., & Merz, T. (2020). Lone wolves in distance learning?: an empirical analysis of the tendency to communicate within student groups. International Journal of Mobile and Blended learning(IJMBL), 12 (1), 82-94.
Kuznetsov, Y. A. (2013). Elements of applied bifurcation theory (Vol. 112). Springer Science & Business Media.
Lam, J. (2014 ). The context of blended learning: The tips blended learning model. Springer International Publishing, Switzerland, 80-92.
Mustapa, K. (2018). Online instructional strategy with different goals orientation on university students' higher order thinking skills. In First Indonesian Communication Forum of Teacher Training and Education Faculty Leaders International Conference on Education 2017 (ICE 2017). Atlantis Press.
Nguyen, H. T., Duong, P. H., & Cambria, E. (2019). Learning short-text semantic similarity with word embeddings and external knowledge sources. Knowledge-Based Systems, 182, 104842.
Owston, R., York, D. N., & Malhotra, T. (2019). Blended learning in large enrolment courses: Student perceptions across four different instructional models. Australasian Journal of Educational Technology, 35(5), 29-45.
Özyurt, Ö., & Özyurt, H. (2015). Individualized learning style based adaptive e-learning environments: Content analysis of the articles published from 2005 to 2014. Elsevier: Computers in Human Behavior, 52(3), 349-358.
Passwords, G. (2012). Effect of blended learning against chemical judging learning outcomes of students independence. Journal of Education and Teaching, 45(3), 241-251.
Rahmawati, R., Lestari, F., & Umam, R. (2019). Analysis of the effectiveness of learning in the use of learning modules against student learning outcomes. Desimal: Jurnal Matematika, 2(3), 233-240.
Reich, S. M., Subrahmanyam, K., & Espinoza, G. (2012). Friending, iming, and hanging out face-to-face: Overlap in adolescents' online and offline social networks. Developmental Psychology, 48 (2), 356-368.
Serhan, D. (2019). Web-based homework systems: students’ perceptions of course interaction and learning in mathematics. International Journal on Social and Education Sciences, 1(2), 57-62.
Shalihah, F., Supramono, S., & Abdullah, A. (2019). Blended learning-based media usage to practice problem solving skills. European Journal of Education Studies. 17(3), 27-43.
Sharif, I. (2012). Effect of blended learning, model motivation and vocational student achievement. Journal of Vocational Education, 2(2), 234-249.
Skocic Mihic, S., Blanusa Troselj, D., & Katic, V. (2019). Influence of in-service preschool teachers’ education on their perceived competences for counselling parents. CEPS Journal, 9(1), 27-43.
Sugiyono. (2016). Educational Research Methods Quantitative, Qualitative, and R & D Approach. Bandung: Alfabeta.
Sutisna, A. (2016). Learning blended learning and model development on equality education program to enhance independence package e-learning. Journal of Educational Technology, 18(3), 156-168.
Tseng, H., Yi, X., & Yeh, H. T. (2019). Learning-related soft skills among online business students in higher education: Grade level and managerial role differences in self-regulation, motivation, and social skill. Computers in Human Behavior, 95(4), 179-186.
Tytler, R. (2003). A window for a purpose: Developing a framework for describing effective science teaching and learning. Research in Science Education, 33(3), 273-298.
Vo, M. H., Zhu, C., & Diep, A. N. (2020). Examining blended learning implementation in hard and soft sciences: a qualitative analysis. International Journal of Research in Education and Science, 6(2), 250-272.
Walter, C. (2016). What are tutors’ experiences with online teaching?: a phenomenographic study. International Journal of Mobile and Blended learning, 8(1), 18-33.
Wicaksono, I., Madlazim, & Wasis, W. (2017). The effectiveness of virtual science teaching model (VS-TM) to improve student’s scientific creativity and concept mastery on senior high school physics subject. Journal of Baltic Science Education, 16(4), 549-561.
Williams, A. E. (2017). Promoting meaningfulness by coupling Bloom’s taxonomy with adult education theory: introducing an applied and interdisciplinary student writing exercise. Transformative Dialogues: Teaching & Learning Journal, 10(3), 1-11.
Zakirman, Z., Lufri, L., & Khairani, K. (2019). Factors influencing the use of lecture methods in learning activities: Teacher perspective. In 1st International Conference on Innovation in Education (ICoIE 2018). Atlantis Press.
Zorluoglu, S. L., & Güven, Ç. (2020). Analysis of 5th grade science learning outcomes and exam questions according to revised Bloom taxonomy. Journal of Educational Issues, 6(1), 58-69.
Zuhairi, A., Adnan, I., & Thaib, D. (2007). Provision of Student Learning Support Services in a Large-Scale Distance Education System at Universitas Terbuka, Indonesia. Online Submission, 8(4), 44-64.
Zupanc, G. K. (2019). Understanding the role of diffusion in synaptic transmission through inquiry-based learning & quantitative reasoning. The American Biology Teacher, 81(6), 435-441.
Downloads
Published
2020-09-25
How to Cite
Budiastra, A. K. (2020). The Effectiveness of Blended and Printed Learning Resources in Improving Science Learning Outcomes of Student Teachers at a Distance University. Advances in Social Sciences Research Journal, 7(9), 435–450. https://doi.org/10.14738/assrj.79.9024
Issue
Section
Articles
License
Authors wishing to include figures, tables, or text passages that have already been published elsewhere are required to obtain permission from the copyright owner(s) for both the print and online format and to include evidence that such permission has been granted when submitting their papers. Any material received without such evidence will be assumed to originate from the authors.
