Final Reflection

It was interesting to see the interaction on Twitter between everyone and the positive feedback everyone who was involved provided. Going through the tweets, I learned a lot about the benefits of openness and sharing in k-12 learning. Moreover, throughout the course, we have engaged in different activities that highlight the benefits of open learning and the opportunities it offers to students to interact with people from different backgrounds. 

Individual Portfolio

Digital Data, Security & Privacy in Educational settings

Modern tracking systems involve assigning students to different levels of the same course, or to a course with a different curriculum that is either more or less demanding. In some schools, student tracking starts with kindergarten screening and continues through high school. IQ and early achievement tests are ways in which some of these schools measure students’ “ability” and determine the trajectory for 12 years of schooling. Moreover, with the advancement of technology, state longitudinal data systems can now track students from pre-K through college and work. An issue raised is the ethical concern of whether such programs online involve tracking and sorting of students that might lead to discrimination, which can occur depending on student data used, the profile used to categorize the student and the recommendations offered. Through this process also, an incredible amount of data is collected from educational systems and as part of educational research. Schools and Districts as well keep detailed data such as academic performance, behavior and educational needs on all their students that can be easily accessed when needed. In addition, applications used for learning by students store information that involves their decision making processes, which can be collected by software developers and researchers. While there are some benefits to these processes such as creation of innovative technology for educational problems, it also poses a significant concern to the privacy of users, including excessive data gathering, unclear security protocols, a lack of transparency, and insufficient policies on data archiving. Furthermore, there is a common concern around students’ information being placed in the wrong hands or put to nefarious uses. These concerns focus mainly around privacy breaches, hacking and the use of data by commercial software developers for marketing purposes. There is also a possibility in which sensitive information e.g. learning disabilities, behavior problems or test scores if accessed, might limit students’ future opportunities. 

These privacy concerns have led to some major policy changes that will prevent students’ data from being misused. Emerging state and federal legislation have put a focus to create a limit on how much data can be collected, how long they can be stored and how they are being used for commercial, research, and other purposes. Such actions include preventing research that is not directed at improving learners’ outcome, making it a requirement for parents to opt in, and requiring institutions to delete student records once they leave. Moreover, student privacy laws restrict types of information collected, limit access by third parties, and improve ways in which data are secured. With proper guidelines, researchers can access the right data that can be used to understand and improve learning and teaching outcomes for all students. But the privacy of students and families must be protected to achieve this.

Bienkowski, M. (2017). Implications of privacy concerns for using student data for research: Panel summary. Workshop on Big Data in Education. Accessed March 4, 2018, from

Burris, C. C., & Garrity, D. T. (2008). Detracking for excellence and equity,” see especially Chap. 2 “What Tracking is and How to Start Dismantling It.” Accessed March 15, 2016, from

Kurshan, B. (2017, July 10). The Elephant in the Room With EdTech Data Privacy. Retrieved July 30, 2020, from 

Regan, P. M., & Jesse, J. (2018). Ethical challenges of edtech, big data and personalized learning: Twenty-first century student sorting and tracking. Ethics and Information Technology, 21, 167-179.

Individual Post #4

How can Twitter harm learners and educators?

Although there are many benefits that come with the use of digital technology i.e. Twitter in classrooms, there are some limitations that come with this. Teachers who have limited training on how to integrate digital literacy into classroom risk compromising the development of their students’ soft skills that could be advantageous in their educational and professional career. Personal privacy concern is also another issue that educators and students have raised as a concern. This can occur when the boundary between students and instructors gets broken causing a negative impact. One study indicated that twitter could harm instructors’ credibility or even get them fired from their job if they post negative or biased tweets. In the study, students argued that twitter can also decrease an instructor’s position of authority and their reputation may be considered more of a student than a professor. Moreover, there were also some concerns raised that use of twitter in classrooms could lead to favoritism or even a romantic relationship between teachers and instructors. In addition, the student/teacher relationships can violate typical classroom and time expectations. Some students would rather keep their relationship with instructors strictly in a classroom setting. Furthermore, students may overstep their bounds and reach out to instructors at unreasonable times or outside work hours. Students were also worried they would miss important announcements from their instructors as some of them may not have twitter accounts or follow too many accounts. Another study by Catholic University of the Sacred Heart in Milan, found that Twitter reduced performance on a standardized tests by about 25 to 40 percent of standard deviation. This problem resulted from students thinking they absorbed more content just from reading the tweets rather than reading actual books. Moreover, students can get distracted on the social media tool, surfing preferred activities, which can have a negative impact on student learning.

Authors, A., & DeGroot, J. (n.d.). Twitter Use and its Effects on Student Perception of Instructor Credibility. Retrieved July 31, 2020, from

Stanley-Becker, I. (2019, May 30). Twitter is eroding your intelligence. Now there’s data to prove it. Retrieved July 31, 2020, from

The 3 biggest Twitter problems for teachers-and how to overcome them. (2017, March 29). Retrieved July 31, 2020, from

Individual Post #2

It has come to my notice that open education has difficulties that are encountered due to different interpretations and perspectives especially to new researchers for instance not knowing where to start and not having a common understanding when people have different starting points. The citation and network approach helps in identifying clusters and themes but it also has limitations such as unavailability of certain texts online and biases in citation practices. Open education also represents an area of study that many people come to from elsewhere but also has disadvantages to a newcomer. Disadvantages to a newcomer can include disconcerting to know where to start since there is no clearly defined disciplinary body at work and it can also lead to amnesia or reinventing the wheel in the field as previous work may be forgotten.

In conclusion as much as open education is of advantage in areas such as choosing educational objectives, organization and sequencing materials, and enhancing motivations, it also has disadvantages such as setting objectives and the role of the teacher. E learning and online education which started in early 1990 to 2000 helped bridge the gap between education and OER. It also helped introduce an influential conversational framework model as a way of analyzing the potential for a technology introduced into the learning process. Though e-learning and OER has major benefits it also has shortcomings such as behaviorism, cognitivism and constructivism.

Arcos, B. (2020, July 14). Openness and education: A beginner’s guide: GO-GN. Retrieved July 31, 2020, from 

Individual Post #1

From the 3 articles, the one written by Regan and Jess, highlighting the ethical concerns that come from edtech applications, stood out the most to me. I initially thought I had an understanding of how data is collected from students, however it was quite appalling to learn the level of data gathered from students at a very young age. As noted in the article, privacy is definitely a huge issue, as edtech involves collection of detailed information about students, teachers, families and administrative details about educational institutions (Regan & Jesse, 2018). While personalized learning applications can be beneficial to students, as it gears towards the student’s learning styles, it shouldn’t come at the cost of them losing the privacy of their information online. Moreover, it was evident that the data being collected was very concerning in the sense that it seemed to be a form of “surveillance” through an “intrusive data” gathering process (Regan & Jesse, 2018). Although this process might have some benefits to teachers, such as providing guidance on how to approach each child, it might cause discrimiantion against others. Under the umbrella of privacy, there are six ethical concerns associated with privacy emphasized in the article that include: information privacy, anonymity, surveillance, autonomy, non-discrimantion and ownership of information (Regan & Jesse, 2018). It is important that each of these ethical concerns be addressed separately to help protect the privacy of students. While I know we can not always have full control of how our data is collected online, we should at least be allowed to know what kind of data is collected in educational institutions, and how it’s used.


Regan, P. M., & Jesse, J. (2018). Ethical challenges of edtech, big data and personalized learning: Twenty-first century student sorting and tracking. Ethics and Information Technology, 21, 167-179.

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