American Journal of Educational Research
ISSN (Print): 2327-6126 ISSN (Online): 2327-6150 Website: Editor-in-chief: Ratko Pavlović
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American Journal of Educational Research. 2018, 6(2), 108-116
DOI: 10.12691/education-6-2-3
Open AccessArticle

Translating Numbers into Feedback: Providing Students with Automatically Generated Feedback

Sebastian Hedtrich1 and Nicole Graulich1,

1Institute of Chemistry Education, Justus-Liebig-University, Gießen, Germany

Pub. Date: February 09, 2018

Cite this paper:
Sebastian Hedtrich and Nicole Graulich. Translating Numbers into Feedback: Providing Students with Automatically Generated Feedback. American Journal of Educational Research. 2018; 6(2):108-116. doi: 10.12691/education-6-2-3


Universities nowadays are confronted with the challenge of offering students sufficient formative feedback about their learning progress. Undergraduates in particular struggle in this almost impersonal learning situation, in contrast to their experience at school. Web-based trainings often do not allow a comparable formative feedback from a teacher, as current Learning Management Systems only offer basal feedback mechanisms. The Learning Management System Analyzation Kit and the Easy Snippet Feedback Edit are software tools that have been developed to overcome this shortcoming. The intuitive design of the software allows teachers to develop small feedback generating programs, which use the educational data of EDM solutions, raw data of the LMS, or just teachers’ individual records to compose individual formative feedback messages for all students. Initial evaluations show that students appreciate this new type of feedback, and that even inexperienced users can easily operate the software.

blended learning automated feedback LMS distance learning

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[1]  Hattie, J., Timperley, H., “The Power of Feedback, Review of Educational Research, 77 (1), 81-112, 2007.
[2]  Hattie, J., “Calibration and confidence, Learning and Instruction, 24, 62-66, 2013.
[3]  Kluger, A. N., DeNisi, A., “Feedback Interventions, Current Directions in Psychological Science, 7 (3), 67-72, 1998.
[4]  Shute, V. J., “Focus on Formative Feedback, Review of Educational Research, 78 (1), 153-189, 2008.
[5]  Bol, L., Hacker, D. J., O'Shea, P., Allen, D., “The Influence of Overt Practice, Achievement Level, and Explanatory Style on Calibration Accuracy and Performance, The Journal of Experimental Education, 73 (4), 269-290, 2005.
[6]  Kruger, J., Dunning, D., “Unskilled and unaware of it, Journal of personality and social psychology, 77 (6), 1121-1134, 1999.
[7]  Seery, M. K., Donnelly, R., “The implementation of pre-lecture resources to reduce in-class cognitive load, British Journal of Educational Technology, 43 (4), 667-677, 2012.
[8]  Yorke, M., “Formative assessment in higher education, Higher Education, 45 (4), 477-501, 2003.
[9]  Fung, F. M., “Using First-Person Perspective Filming Techniques for a Chemistry Laboratory Demonstration To Facilitate a Flipped Pre-Lab, Journal of Chemical Education, 92 (9), 1518-1521, 2015.
[10]  Sanger, M. J., Phelps, A. J., Fienhold, J., “Using a Computer Animation to Improve Students' Conceptual Understanding of a Can-Crushing Demonstration, Journal of Chemical Education, 77 (11), 1517, 2000.
[11]  Fautch, J. M., “The flipped classroom for teaching organic chemistry in small classes, Chem. Educ. Res. Pract., 16 (1), 179-186, 2015.
[12]  Espasa, A., Meneses, J., “Analysing feedback processes in an online teaching and learning environment, Higher Education, 59 (3), 277-292, 2010.
[13]  Gikandi, J. W., Morrow, D., Davis, N. E., “Online formative assessment in higher education, Computers & Education, 57 (4), 2333-2351, 2011.
[14]  Zorrilla, M., Menasalvas, E., Marín, D., Mora, E., Segovia, J., “Web Usage Mining Project for Improving Web-Based Learning Sites in Computer Aided Systems Theory - EUROCAST 2005: 10th International Conference on Computer Aided Systems Theory, Las Palmas de Gran Canaria, Spain, February 7 - 11, 2005, Revised Selected Papers, Springer Berlin Heidelberg, 205-210.
[15]  Martín-Blas, T., Serrano-Fernández, A., “The role of new technologies in the learning process, Computers & Education, 52 (1), 35-44, 2009.
[16]  Dutt, A., “Clustering Algorithms Applied in Educational Data Mining, International Journal of Information and Electronics Engineering, 2015.
[17]  Long, P., Siemens, G., “Penetrating the Fog: Analytics in Learing and Education, Educause Review, 46 (5), 31-40, 2011.
[18]  Romero, C., Ventura, S., García, E., “Data mining in course management systems, Computers & Education, 51 (1), 368-384, 2008.
[19]  Fritz, J., “Classroom walls that talk, The Internet and Higher Education, 14 (2), 89-97, 2011.
[20]  Macfadyen, L. P., Dawson, S., “Mining LMS data to develop an “early warning system” for educators, Computers & Education, 54 (2), 588-599, 2010.
[21]  Mohamad, S. K., Tasir, Z., “Educational Data Mining, Procedia - Social and Behavioral Sciences, 97, 320-324, 2013.
[22]  Dangauthier, P., Herbrich, R., Minka, T., Graepel, T., “TrueSkill Through Time in Advances in Neural Information Processing Systems 20, Curran Associates, Inc, 337-344.
[23]  Pelánek, R., “Applications of the Elo rating system in adaptive educational systems, Computers & Education, 98, 169-179, 2016.
[24]  Hedtrich, S., Graulich, N., “Crossing Boundaries in Electronic Learning in Computer-Aided Data Analysis in Chemical Education Research (CADACER), Oxford University Press, 21-28.
[25]  Liu, O. L., Rios, J. A., Heilman, M., Gerard, L., Linn, M. C., “Validation of automated scoring of science assessments, Journal of Research in Science Teaching, 53 (2), 215-233, 2016.
[26]  Chambers, K. A., Blake, B., “Enhancing Student Performance in First-Semester General Chemistry Using Active Feedback through the World Wide Web, Journal of Chemical Education, 84 (7), 1130, 2007.
[27]  Denton, P., Madden, J., Roberts, M., Rowe, P., “Students' response to traditional and computer-assisted formative feedback, British Journal of Educational Technology, 39 (3), 486-500, 2008.
[28]  La Muñoz de Peña, A., González-Gómez, D., La Muñoz de Peña, D., Gómez-Estern, F., Sánchez Sequedo, M., “Automatic Web-Based Grading System, Journal of Chemical Education, 90 (3), 308-314, 2013.
[29]  Debuse, J. C. W., Lawley, M., “Benefits and drawbacks of computer-based assessment and feedback systems, British Journal of Educational Technology, 47 (2), 294-301, 2016.
[30]  Sáez-López, J.-M., Román-González, M., Vázquez-Cano, E., “Visual programming languages integrated across the curriculum in elementary school, Computers & Education, 97, 129-141, 2016.
[31]  Cohen, J., Statistical power analysis for the behavioral sciences, L. Erlbaum Associates, 1988.
[32]  Hattie, J. A. C., Visible learning, Routledge, 2010.
[33]  Rowe, G., Wright, G., “The Delphi technique as a forecasting tool, International Journal of Forecasting, 15 (4), 353-375, 1999.
[34]  Green, K., Armstrong, J. S., Graefe, A., “Methods to Elicit Forecasts from Groups, Foresight: The International Journal of Applied Forecasting (8), 17-20, 2007.
[35]  Rowe, G., Wright, G., “The Delphi technique, Technological Forecasting and Social Change, 78 (9), 1487-1490, 2011.
[36]  Skulmoski, G. J., Hartman, F. T., Krahn, J., “The Delphi Method for Graduate Research, Journal of Information Technology Education: Research, 6, 1-21, 2007.