The Extent to which the Policy Addresses the Educational Issue across Student Populations and Develops Ways to Maximize Learning Outcomes

The proposed measures extensively address the issues surrounding accountability in online education; however, it should be noted that this policy does not address larger issues in the future of online education such as the increasing digital divide, in which certain students have access to electronic devices while others do not – especially at home, the policy does thoroughly examine measures to improve the accountability of virtual classrooms by formatting assessments differently, suggesting methods to alter teaching techniques for instructors of virtual classrooms, as well as provide strategies to verify student identification in virtual classrooms to prevent academic dishonesty.

In regards to assessing students differently for the virtual learning environment, Kerton and Cervato (2014) recommend setting time limitation on formative and summative assessments as well as format questions to encourage mastery of content area, skill sets, and curriculum so that students would not be as likely to spend time searching through web browsers for answers because exams are going to be inevitably open note. In order to combat the unavoidable reality of open notes, virtual classrooms need to make use of virtual proctoring software such as VProctor to prevent dishonest academic activity such as “opening another browser window, talking on a phone, talking to someone else in the room, or using a book (Venable, 2013).”

Furthermore, to ensure that the student receiving credit for the virtual course is in fact the same student that is doing the work for the virtual course, online programs need to take advantage of strategies to verify student identity such as Strayer University’s random multiple choice challenge questions such as “prior street address or zip code” to verify student identities , Proctor University’s live proctor system which checks on students via web camera and photo identification, and even eduKan’s biometric recognition program that utilizes fingerprinting, voice recognition, retinal scans, keystroke patterns, etc. (Venable, 2013).

The proposed measures also include progress models to hold students accountable for their attendance and truancy by modeling the the attendance system used by MVHS schools, which divided progress towards credit completion through the completion of various assignments (Archambault, Kennedy, & Bender).

In order to maximize learning outcomes, the proposed methods encourage teachers, researchers, educators, and administrators involved in online education to collaborate their research, findings, and strategies through open licensed software as well as to undergo preparation programs that would ensure teachers meet the standards set out in the iNACOL’s National Standards for Quality Online Teaching (2011).

Archambault, L., K. Kennedy, and S. Bender. 2013. Cyber-truancy: Addressing issues of attendance in the digital age. Journal of Research on Technology in Education 46 (1): 1–28

International Association for K-12 Online Learning. (2011, October 1). National Standards for Quality Online Teaching (Rep. No. 2). Retrieved April 25, 2016, from International Association for K-12 Online Learning website:

Kerton, C., & Cervato, C. (2014). Assessment in Online Learning–It’s a Matter of Time. Journal Of College Science Teaching, 43(4), 20-25.

Venable, M. (2013, August 16). Online Student Verification: Is that you? Are you there? – Retrieved April 25, 2016, from


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