Digital Assessment of Learning: Promoting Academic Integrity in Online Assessments

ED 6380 - Spec Topics in Ed Tech

In recent years, the use of digital technologies in education has grown rapidly, and with it, the use of digital assessment of learning. As more and more educational institutions move towards online learning and digital assessment, maintaining academic integrity has become a major concern for educators and administrators alike.

Academic integrity is a fundamental principle of education that refers to the honest and ethical behavior of students and teachers in academic work. In traditional classroom settings, academic integrity is maintained through various means, such as teacher supervision, honor codes, and the use of proctored exams. One of the key challenges of online assessments is the prevalence of online cheating. Online cheating refers to any behavior by students that violates academic integrity in the digital learning environment. Some common forms of online cheating include plagiarism, using unauthorized materials during exams, and collaborating with other students without permission.

As communicated by Feeney (2017) in his article, "How to Prevent Cheating During Online Tests," he reiterates the importance of establishing a culture of honesty in the classroom, for example, if students become aware that classmates are getting away with cheating, this behavior will spread to other members of the class very quickly, thus perpetuating a culture of dishonesty where students feel they must cheat to remain competitive.  Feeney (2017) further suggests that teachers should start the course of the school year by having an open conversation with students about academic integrity. Students need to understand the school’s definition of academic dishonesty or cheating.

Computer-Based Grading

The article “An Evaluation of Assessment- Oriented Computer Based Text Analysis Paradigms” provides a classification of computer-based writing assessment (CBTA) programs based on their intent. Computer-based text analysis programs are classified into two categories: summative assessment and formative assessment. Most CBTA programs were developed to assess written text and to provide a summary score (summative assessment). Some applications, however, are used primarily as a learning environment designed to assist students in learning how to write (formative assessment) as well as possibly providing summative assessment. (Aken, 2017)

Summative assessment applications are primarily designed to provide a summary score for written texts. CBTA Summative assessment evaluates skills and knowledge acquired at a “point in time” and does not provide detailed feedback to the learner. ​ Examples of applications primarily designed for summative assessment include Intelli metric, BETSY, Web Grader, Write Placer, PEG, Alaska Assessment Project, Intelligent Essay Assessor (IEA), C-Rater, Intelligent Essay Marking System, SEAR, and IFDSSEA. (Aken, 2017) On the other hand, Formative assessment applications are primarily designed to assist students in learning how to write. CBTA formative assessment provides feedback to the learner and guides instruction by the teacher. The teachers then focus on providing immediate, detailed, and specific feedback to help students improve their writing skills, with the primary purpose being to support learning. Examples of applications that can be utilized for formative assessment include My Access! Criterion, Write to Learn, Essay Rater, Calibrated Peer Review (CPR), SA Grader, Glencoe Online Essay Grader, Writer's Workbench, Di GIMS Online, Semi-Automatic Grader, ETIPS, Mark IT, Microsoft Word, My Comp Lab, Sentence works, Choices, and Paperless School free text Marking Engine. (Aken, 2017)

According to O’Donnell (2018) in the article “Computers are now grading essays on Ohio’s state tests,” Ohio started using the American Institute for Research in 2015 to provide and score state tests, and Artificial Intelligence (AI) programs have increasingly taken over grading. O’Donnell (2018) further reported that computers are now scoring the entire test for approximately 75% of Ohio students, as confirmed and communicated by State Superintendent Paolo De Maria and state testing official Brian Roget when they told the state school board recently. Even though multiple testing organizations, including Pearson, McGraw Hill, and Educational Testing Service, have developed automated scoring systems for student essays, any introduction of technology, such as grading of student tests, has generated skepticism and concerns from board members, politicians, educators, etc.

The Ohio State Superintendent, Paolo De Maria, in support of computers scoring tests, said, “The motivation is to be as effective and efficient and accurate in grading all these things.” He further specifies that AI is making this grading process more consistent and fairer, plus he states that it saves time and, in the long run, money. The change to computerized grading was not widely publicized, nor were primary stakeholders informed, thus this surprised legislators, school boards, and school district administrators, creating skepticism and/or distrust, leading school districts to monitor scores and find irregularities carefully. Most of the concerns focused on whether machines could accurately grade essays, especially for tests that would have a significant impact on student’s academic progress or promotions to the next grade level. (O’Donnell, 2018)

Big Data

The authors of the article “Big Data Comes to School: Implications for Learning, Assessment & Research” imply that BIG data has become a much-used phrase in public discourse, optimistically as well as controversially. In more optimistic moments, big data heralds “a revolution that will transform how we live, work, and think” (Mayer-Schnberger & Cukier, 2013).

The authors assert that instruction can be personalized, and with improvements in big data, the notion is that it could revolutionize education. Data has and will continue to improve analytics, thus giving teachers better information that will help them understand their students' learning patterns, giving them the tools to individualize instruction to meet their defined needs, challenges, etc. Also, as it relates to formative assessment, big data will have the capability for ongoing and actual formative assessment. Big data has changed how teachers approach their job because by collecting and analyzing data generated by student writing assignments and other relevant activities, teachers have the tools to provide immediate feedback and revise instructions to improve learning outcomes for the students. Teachers' traditional approach of separating instruction and assessment has shifted because assessments are now a part of almost every learning process and allow teachers to provide ongoing feedback from a more informed instructional decision-making level.

As the area of education embraces big data, the focus has opened new fields of study in educational data mining and learning analytics. The traditional top/down models of school hierarchical structures have been disrupted because administrators and researchers need to realign themselves as data collaborators alongside both teachers and learners. Finally, researchers and data infrastructures have encountered challenges around data access, data models, and data privacy and there is a need to address and make use of the potential of big data in education. All these takeaways reiterate the potential of big data in education, but there needs to be more research and development in this area. This is an area where I would like to know more information or have further questions to research.

Canvas

According to the College of Marin Online Learning (2024), Canvas is a course management system (CMS) that is used for all online, hybrid, and web-enhanced courses and also connects some of the digital tools and resources teachers use into one simple place. After viewing the video on standards-based grading with canvas outcomes, the presenter’s goal was to provide a quick overview depicting the software capabilities and introduce software navigation tools.

Canvas, once the teacher learns how to set up the classroom structure and define the skills, content, assessment benchmarks, etc., is an excellent tool to facilitate classroom learning. For students, students can see their progress in real-time, letting them know their level of mastery as it relates to any one of the learning objectives preset by the teachers. Teachers also can view student progress in real-time, identify the areas where students are challenged to master the learning objectives of the lessons, and pivot and change or revise the teaching approach so that it aligns with the student's needs.

 After reviewing Canvas, I can see the advantages of using this learning management system, and providing instantaneous information is key to providing feedback and another type of assistance. On the downside, understanding databases, their structure, and setting up the parameters for what you want to extract is a process that involves intensive training, and the learning curve can be significant.

Additional Resource

Canvas Overview (2024) Tutorial Video Series, College of Marin Online Learning. https://ol.marin.edu/canvas-overview 19, DOI: 10.1177/2332858416641907, http://ero.sagepub.com

References

Aken, A. (2017) An Evaluation of Assessment-Oriented Computer-Based Text Analysis Paradigms. Higher Education Research, 2(4), 111-116.

Canvas Overview (2024) Tutorial Video Series, College of Marin Online Learning. https://ol.marin.edu/canvas-overview

19, DOI: 10.1177/2332858416641907, http://ero.sagepub.com

Cope, B., & Kalantzis, M. (2016). Big data comes to school. AERA Open, 2(2), 1-19. https://doi.org/10.1177/2332858416641907

Feeney, J. (2017) How to Prevent Cheating During Online Tests. Evolving Ed. https://www.schoology.com/blog/how-prevent-cheating-during-online-tests

Mayer-Schnberger, V., & Cukier, K. N. (2013). Big data: a revolution that will transform how we live, work, and think. Choice Reviews Online, 50(12), 50–6804. https://doi.org/10.5860/choice.50-6804

O’Donnell, P. O. P. (2018). Computers are now grading essays on Ohio’s state tests. Plain Dealer, The: Web Edition Articles. Cleveland.  https://www.cleveland.com/metro/2018/03/computers_are_now_grading_essays_on_ohios_state_tests_your_ch.html#:~:text=Computers%20are%20now%20scoring%20the,help%20verify%20the%20computer’s%20work.