Quantitative Analysis Between Blackboard Learning Management System and Students’ Learning
by Charles Darko * 
Department of Materials, The University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
* Author to whom correspondence should be addressed.
Journal of Engineering Research and Sciences, Volume 1, Issue 5, Page # 119-133, 2022; DOI: 10.55708/js0105013
Keywords: Blackboard Learning Management System, Lecture Engagement, Material Science and Engineering students, Cognitive learning theory
Received: 23 January 2022, Revised: 19 April 2022, Accepted: 23 April 2022, Published Online: 12 May 2022
APA Style
Darko, C. (2022). Quantitative Analysis Between Blackboard Learning Management System and Students’ Learning. Journal of Engineering Research and Sciences, 1(5), 119–133. https://doi.org/10.55708/js0105013
Chicago/Turabian Style
Darko, Charles. “Quantitative Analysis Between Blackboard Learning Management System and Students’ Learning.” Journal of Engineering Research and Sciences 1, no. 5 (May 1, 2022): 119–33. https://doi.org/10.55708/js0105013.
IEEE Style
C. Darko, “Quantitative Analysis Between Blackboard Learning Management System and Students’ Learning,” Journal of Engineering Research and Sciences, vol. 1, no. 5, pp. 119–133, May 2022, doi: 10.55708/js0105013.
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Abstract
Proper use of the Blackboard Learning Management System (LMS) motivates students to engage with their studies but the students within Material Science and Engineering (MSE) often use these LMSs to copy mathematical derivations, scientific information and submit coursework tasks without spending much time interacting with the system. Quantitatively, there is a piece of missing information on how interaction with the Blackboard LMS influences students’ performances. Statistical evaluations were made by using the average times students spent on Blackboard and their final examination grades for their three-year Bachelor’s degree period. There was a linear positive correlation between the time students spent on the LMS and their grades. Observations also show that students engage more with LMS at certain periods within a week. It was recognised that the more students engage with the Blackboard, the more they construct information for themselves. This result provides a quantitative analysis that gives evidence of how time spent on LMS supports students’ learning.
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- H Duin, J. Tham, “The current state of analytics: Implications for learning management system (LMS) use in writing pedagogy,” Computers and Composition, vol. 55, p. 102544,. doi.org/10.1016/j.compcom.2020.102544
- R. Rabiman, M. Nurtanto, N. Kholifah, “Design and Development E-Learning System by Learning Management System (LMS) in Vocational Education,” Online Submission, vol. 9(, pp. 1059-1063, 2020.
- H. Ghapanchi, A. Purarjomandlangrudi, A. McAndrew, Y. Miao, “Investigating the impact of space design, visual attractiveness and perceived instructor presence on student adoption of learning management systems,” Education and Information Technologies, vol. 25, pp. 5053-5066, doi.org/10.1007/s10639-020-10204-5.
- Y. Su, C. H. Chen, “Investigating university students’ attitude and intention to use a learning management system from a self-determination perspective,” Innovations in Education and Teaching International, pp.1-10, doi.org/10.1080/14703297.2020.1835688.
- R. Cerezo, M. Sánchez-Santillán, M. P. Paule-Ruiz, J. C. Núñez, “Students’ LMS interaction patterns and their relationship with achievement: A case study in higher education,” Computers & Education, vol. 96, pp. 42-54, 2016, doi.org/10.1016/j.compedu.2016.02.006.
- Y. Li, C. C. Tsai, “Accessing online learning material: Quantitative behavior patterns and their effects on motivation and learning performance,” Computers & Education, vol. 114, 286-297, 2017, doi.org/10.1016/j.compedu.2017.07.007.
- H. L. Koh, R. Y. P. Kan, “Perceptions of learning management system quality, satisfaction, and usage: Differences among students of the arts,” Australasian Journal of Educational Technology, vol. 36, pp. 26-40, 2020, doi.org/10.14742/ajet.5187
- Baikadi, C. Demmans Epp, C. D. Schunn, “ Participating by activity or by week in MOOCs,” Information and Learning Science, 2018, doi.org/10.1108/ILS-04-2018-0033.
- D. Epp, K. Phirangee, J. Hewitt,C. A. Perfetti, “Learning management system and course influences on student actions and learning experiences,” Educational Technology Research and Development, vol. 68, pp. 3263-3297, 2020, doi.org/10.1007/s11423-020-09821-1.
- Juarez Santiago, J. M. Olivares Ramirez, J. Rodríguez-Reséndiz, A..Dector, R. Garcia Garcia, J. E. González-Durán, F. Ferriol Sanchez, “Learning Management System-Based Evaluation to Determine Academic Efficiency Performance,”. Sustainability, vol. 12, p. 4256, 2020, doi.org/10.3390/su12104256.
- H. S. Simanullang, J. Rajagukguk, (2020). Learning Management System (LMS) Based On Moodle To Improve Students Learning Activity. In Journal of Physics: Conference Series, vol. 1462, p. 012067. IOP Publishing. 2020, doi.org/10.1088/1742-6596/1462/1/012067.
- Tseng, “An exploratory study of students’ perceptions of learning management system utilisation and learning community,” Research in Learning Technology, vol. 28, 2020, doi.org/10.25304/rlt.v28.2423.
- Vallone, E. Dell’Aquila, M. C. Zurlo, D. Marocco, “ACCORD’e-Platform: development and evaluation of an innovative multicultural training for school professionals,” In PSYCHOBIT, 2020.
- Ferguson, E. Scanlon, L. Harris, ”Developing a strategic approach to MOOCs,” Journal of Interactive Media in Education, vol. 1, p. 21, 2016. For more information, see https://doi.org/10.5334/jime.439.
- B. Mpungose, S. B. Khoza, “Postgraduate students’ experiences on the use of Moodle and Canvas learning management system,” Technology, Knowledge and Learning, pp. 1-16, 2020, doi.org/10.1007/s10758-020-09475-1.
- Almoeather, “Effectiveness of Blackboard and Edmodo in self-regulated learning satisfaction, “Turkish Online Journal of Distance Education (TOJDE), vol. 21, 2020, doi.org/10.17718/tojde.728140.
- Conley, Y. Earnshaw, G. McWatters, “Examining Course Layouts in Blackboard: Using Eye-Tracking to Evaluate Usability in a Learning Management System,” International Journal of Human–Computer Interaction, vol. 36, pp. 373-385, 2020, doi.org/10.1080/10447318.2019.1644841.
- Naim, F. Alahmari, “Reference Model of E-learning and Quality to Establish Interoperability in Higher Education Systems,“ International Journal of Emerging Technologies in Learning (iJET), vol. 15, pp. 15-28, 2020, doi.org/10.3991/ijet.v15i02.11605.
- Romanov, A. Nevgi, “Do medical students watch video clips in eLearning and do these facilitate learning?” Medical teacher, vol. 29, pp. 490-494, 2007, doi.org/10.1080/01421590701542119.
- S. Liaw, “Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system,” Computers & education, vol. 51, pp. 864-873, 2008, doi.org/10.1016/j.compedu.2007.09.005.
- Martin, “Blackboard as the learning management system of a computer literacy course,” Journal of Online Learning and Teaching, vol. 4, pp. 138-145, 2008.
- Heirdsfield, S. Walker, M. Tambyah, D. Beutel, “Blackboard as an online learning environment: What do teacher education students and staff think?” Australian Journal of Teacher Education (Online), vol. 36, p. 1, 2011, doi.org/10.14221/ajte.2011v36n7.4.
- Machado, E. Tao, “ Blackboard vs. Moodle: Comparing user experience of learning management systems,” In 2007 IEEE 37th annual frontiers in education conference-global engineering: Knowledge without borders, opportunities without passports (IEEE), pp. S4J-7, 2007, doi.org/10.1109/fie.2007.4417910.
- Biswas, “Schoology-supported classroom management: A curriculum review,” Northwest Journal of Teacher Education, vol. 11, p. 12, 2013, doi.org/10.15760/nwjte.2013.11.2.12.
- S. Sicat, “Enhancing college students’ proficiency in business writing via schoology,” International Journal of Education and Research, vol. 3, pp. 159-178, 2015.
- Romero, S. Ventura, “Educational data mining: a review of the state of the art. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 40, pp. 601-618, 2010.
- Calafiore, D. S. Damianov, “The effect of time spent online on student achievement in online economics and finance courses,” The Journal of Economic Education, vol. 42, pp. 209-223, 2011, doi.org/10.1080/00220485.2011.581934.
- R. Esterby, “Trend analysis methods for environmental data,” Environmetrics, vol. 4, pp. 459-481, 1993, doi.org/10.1002/env.3170040407.
- Kivikunnas, “Overview of process trend analysis methods and applications,” In ERUDIT Workshop on Applications in Pulp and Paper Industry, 395-408, 1998.
- Hess, H. Iyer, W. Malm, “Linear trend analysis: a comparison of methods,” Atmospheric Environment, vol. 35, pp. 5211-5222, 2001, doi.org/10.1016/s1352-2310(01)00342-9.
- Educba, “Moving average formula,” 2020. For more information, see https://www.educba.com/moving-average-formula/.
- R. Derrick, B. T. Bates, J. S. Dufek, “Evaluation of time-series data sets using the Pearson product-moment correlation coefficient,” Medicine and science in sports and exercise, vol. 26, pp. 919-928, 1994, doi.org/10.1249/00005768-199407000-00018.
- T. Puth, M. Neuhäuser, G. D. Ruxton, “Effective use of Pearson’s product–moment correlation coefficient,” Animal behaviour, vol. 93, pp. 183-189, 2014, doi.org/10.1016/j.anbehav.2014.05.003.
- Wolfram Mathworld, “Correlation Coefficient,” 2020. For more information, see https://mathworld.wolfram.com/CorrelationCoefficient.html/.
- Sweller, P. Chandler, “Why some material is difficult to learn,” Cognition and instruction, vol. 12, pp. 185-233, 1994, doi.org/10.1207/s1532690xci1203_1.
- S. Yeung, “Cognitive load and learner expertise: Split-attention and redundancy effects in reading comprehension tasks with vocabulary definitions,” The Journal of Experimental Education, vol. 67, pp. 197-217, 1999, doi:10.1080/00220979909598353.
- Carvalho, N. Areal, J. Silva, “Students’ perceptions of Blackboard and Moodle in a Portuguese university,” British Journal of Educational Technology, vol. 42, pp. 824-841, 2011, doi:10.1111/j.1467-8535.2010.01097.x.
- L. Larkin, S. I. Belson, “Blackboard technologies: A vehicle to promote student motivation and learning in physics,” Journal of STEM Education: Innovations and Research, vol. 6., 2005.
- M. Al Meajel, T. A. Sharadgah, “Barriers to using the Blackboard system in teaching and learning: Faculty perceptions,” Technology, Knowledge and Learning, vol. 23, pp. 351-366, 2015, doi.org/10.1007/s10758-017-9323-2.
- Tange, “Caught in the Tower of Babel: university lecturers’ experiences with internationalisation,” Language and Intercultural Communication, vol. 10, pp. 137-149, 2010, doi.org/10.1080/14708470903342138.
- Heaton‐Shrestha, C. Gipps, P. Edirisingha, T. Linsey, “Learning and e‐learning in HE: the relationship between student learning style and VLE use, “ Research Papers in Education, vol. 22, pp. 443-464, 2007, doi.org/10.1080/02671520701651797.
- Graf, T. C. Liu, “Analysis of learners’ navigational behaviour and their learning styles in an online course,” Journal of Computer Assisted Learning, vol. 26, pp. 116-131, 2010, doi:10.1111/j.1365-2729.2009.00336.x.
- Preidys, L. Sakalauskas, “Analysis of students’ study activities in virtual learning environments using data mining methods,” Technological and economic development of economy, vol. 16, pp. 94-108, 2010, doi.org/10.3846/tede.2010.06.
- Y. Huang, S. W. Lin, T. K. Huang, “What type of learning style leads to online participation in the mixed-mode e-learning environment? A study of software usage instruction,” Computers & Education, vol. 58, pp. 338-349, 2012, doi.org/10.1016/j.compedu.2011.08.003.
- Kashima, S. Matsumoto, “Estimating the difficulty of exercises for inactive students in user-based e-learning,” In Iaeng Transactions On Engineering Technologies, vol. 7, pp. 103-114, 2012, doi.org/10.1142/9789814390019_0008.
- F. Nyabawa, “Technology in Learning: Blackboard Usage & Its Impact on Academic Performance,” International Journal of Humanities and Management Sciences (IJHMS), vol. 4, 2016. For more information, see http://www.isaet.org/images/extraimages/P1216204.pdf..
- H. Wu, H. C. Hsiao, P. L., Wu, C. H. Lin, S. H. Huang, “Investigating the learning‐theory foundations of game‐based learning: a meta‐analysis.,” Journal of Computer Assisted Learning, vol. 28, pp. 265-279, 2012, doi:10.1111/j.1365-2729.2011.00437.x.
- J. Vogel‐Walcutt, J. B. Gebrim, C. Bowers, T. M. Carper, D. Nicholson, “Cognitive load theory vs. constructivist approaches: which best leads to efficient, deep learning?,” Journal of Computer Assisted Learning, vol. 27, pp. 133-145, 2011, doi:10.1111/j.1365-2729.2010.00381.x.
- G. Wolff, M. R. Dosdall, “Weighing the risks of excessive participation in asynchronous online discussions against the benefits of robust participation,” MERLOT Journal of Online Learning and Teaching, vol. 6, pp. 55-61, 2010.
- A. Chalmers, “The role of cognitive theory in human–computer interface,” Computers in human behavior, vol. 19, pp. 593-607, 2003, doi: 10.1016/S0747-5632(02)00086-9.
- Debue, N. Ou, C. van de Leemput, “An investigation of using a tablet computer for searching on the web and the influence of cognitive load,” Tutorials in Quantitative Methods for Psychology, vol. 16, pp. 226-239, 2020, doi: 10.20982/tqmp.16.3.p226.
- Biedert, G. Buscher, A. Dengel, “The eyebook–using eye tracking to enhance the reading experience,” Informatik-Spektrum, vol. 33, pp. 272-281, 2010, doi: 10.1007/s00287-009-0381-2.
- Carrasco, N. M. Hanning, “Visual Perception: Attending beyond the Eyes’ Reach,” Current Biology, vol. 30, pp. R1322-R1324, 2020, doi: 10.1016/j.cub.2020.08.095.
- B. Mills, L. J. Weldon, “Reading text from computer screens,” ACM Computing Surveys (CSUR), vol. 19, pp. 329-357, 1987, doi: 10.1145/45075.46162.
- Kim, M. J. Albers, “Web design issues when searching for information in a small screen display,” In Proceedings of the 19th annual international conference on Computer documentation, pp. 193-200, 2001, doi: 10.1145/501516.501555.
- Dillon, “Reading from paper versus screens: A critical review of the empirical literature,” Ergonomics, vol. 35, pp. 1297-1326, 1992, doi: 10.1080/00140139208967394.
- W. Satzinger, “‘The effects of conceptual consistency on the end user’s mental models of multiple applications,” Journal of Organizational and End User Computing (JOEUC), vol. 10, pp. 3-15, 1998.
- C. Bartlett, F. C. Bartlett, “Remembering: A study in experimental and social psychology,” Cambridge University Press, 1995.
- Bernstein, “Essentials of psychology,” Cengage learning, 2018..
- S. McNamara, “Effects of prior knowledge on the generation advantage: Calculators versus calculation to learn simple multiplication,” Journal of Educational Psychology, vol. 87, p. 307, 1995, doi: 10.1037/0022-0663.87.2.307.
- Nichols, “Reading and studying on the screen: An overview of literature towards good learning design practice,” Journal of Open, Flexible, and Distance Learning, vol. 20, pp. 33-43, 2016.
- DeStefano, J. –A. LeFevre, “Cognitive load in hypertext reading: A review,” Computers in Human Behavior, vol. 23, pp. 1616–1641, 2007, doi: 10.1016/j.chb.2005.08.012.
- Lauterman, R. Ackerman, “Overcoming screen inferiority in learning and calibration,” Computers in Human Behavior, vol. 35, pp. 455–463, 2014, doi: 10.1016/j.chb.2014.02.046.
- Mangen, B. R. Walgermo, K. Brønnick, “Reading linear texts on paper versus computer screen: Effects on reading comprehension,” International Journal of Educational Research, vol. 58, pp. 61–68, 2013, doi: 10.1016/j.ijer.2012.12.002.
- Wästlund, H. Reinikka, T. Norlander, T. Archer, “Effects of VDT and paper presentation on consumption and production of information: Psychological and physiological factors,” Computers in Human Behavior, vol. 21, pp. 377–394, 2005, doi: 10.1016/j.chb.2004.02.007.
- Wästlund, T. Norlander, T. Archer, “The effect of page layout on mental workload: A dual-task experiment,” Computers in Human Behavior, vol. 24, pp. 1229–1245, 2008, doi: 10.1016/j.chb.2007.05.001.
- M. Heines, Screen design strategies for computer-assisted instruction. Digital Press, 1984.
- Larissa, “What Are the Eyes and How Do They Work?,” KidsHealth, 2019. For more information, see https://kidshealth.org/en/parents/eyes.html#:~:text=The%20retina%20(the%20soft%2C%20light,sensitive%20to%20light%20than%20cones..
- J. Rozell, W. L. Gardner III, “Cognitive, motivation, and affective processes associated with computer-related performance: a path analysis,” Computers in Human behavior, vol. 16, pp. 199-222, 2000, doi: 10.1016/S0747-5632(99)00054-0.
- H. Dambrot, S. M. Silling, A. Zook, “Psychology of computer use: II. Sex differences in prediction of course grades in a computer language course,” Perceptual and Motor Skills, vol. 66, pp. 627-636, 1998, doi: 10.2466/pms.1988.66.2.627.
- Mitra, “Categories of computer use and their relationships with attitudes toward computers,” Journal of Research on computing in Education, vol. 30, pp. 281-295, 1998, doi: 10.1080/08886504.1998.10782227.
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