Category: papers Page 2 of 6

Teaching During a Pandemic: Spring Transition, Fall Continuation, Winter Evaluation

Informed by survey studies using nationally representative samples, in a recent project we examined the nature and magnitude of remote approaches to teaching and learning at three points in time:

  • April 2020: The pivot to emergency remote teaching was well underway.
  • August 2020: Prepping and planning for the fall offerings.
  • December 2020: Looking back at the fall term.

Some of the big picture findings include the following

  • agility and resilience in the face of numerous and ongoing challenges over the time period under investigation
  • the development of a new appreciation of and understanding about online education
  • growing reliance on technology
  • equity as a focal point of interest and concern
  • flexibility as a design feature that of interest and relevance

 

The report is CC-BY licensed and is available at: Johnson, N., Seaman, J. and Veletsianos, G. (2021) Teaching during a pandemic: Spring Transition, Fall Continuation, Winter Evaluation Bay View Analytics: Oakland CA, March 22, pp. 53.

 

 

How should we respond to the life-altering crises that education is facing?

Below is the the pre-published version of a short reflection I wrote for Distance Education, published here for posterity. The paper is Veletsianos, G. (2020). How should we respond to the life-altering crises that education is facing? Distance Education, 41(4), 1-3. https://doi.org/10.1080/01587919.2020.1825066

Abstract

Prior literature suggests that to address the problems facing education, researchers and practitioners of online and flexible learning should avoid placing too much emphasis on the potential of technology and consult the history and literature of the field. In this reflective article, I argue that in addition to these activities, we should expand our efforts to broaden the reach and impact of our field and engage in speculative work that asks: What should the future of digital, online, and flexible education look like?

Introduction

“In this increasingly unstable world, crises potentially impact our education systems. This will be true whether the crisis is caused by the circulation of a new pathogen, or something else entirely: hurricanes, flooding or wildfire, now more common due to climate change. We have before us a stark reminder that we should approach the promises of technological solutions with caution. Flexible and resilient educational systems require more than tools. They demand collaboration, care, preparation, expertise, resources and learning lessons from the past. (Houlden & Veletsianos, 2020)”

We wrote the sentences above in March 2020, 2 weeks before educational institutions in North America transitioned to remote education in an attempt to influence practitioners’ and researchers’ responses to the life-altering crises that education is facing. We were hoping to convince readers that even though technology may enable institutions of education to engage in some semblance of educational continuity, technology will not fix the crises facing our educational systems. Such reasoning flows from a long line of scholarship that details the problems of technological determinism and solutionism in our field (e.g., Bayne, 2015; Oliver, 2011; Tennyson 1994), urges researchers and practitioners to avoid placing too much emphasis on the potential of technology (e.g., Selwyn, 2011), and encourages us to heed the lessons embedded in the history of the field (e.g., Watters, 2014; Weller, 2020). Similar arguments are included in this issue of Distance Education as well. Baggaley, for instance, argues that “the surest way to make online learning effective is to consult the decades of practical experience in the distance education literature.” But what may be some additional responses to such life-altering crises as COVID-19 and climate change?

One possible response may include efforts to broaden the reach and impact of the distance and flexible education literature, as well as literature present in related fields, such as instructional design and technology, learning analytics, and the learning sciences. Such efforts may address limitations that restrict the literature’s helpfulness, applicability, and accessibility. For instance, the literature suffers from a problem of access. Much of our literature, like the literature of other fields, is written for researchers rather than practitioners, and much of it is locked behind paywalls (like this reflection). One set of responses, therefore, may be to refine and rethink the ways our own scholarship is accessed. For instance, at an individual level, we might strive to make our own articles available in open ways, expand our public outreach, engage in more practice-oriented scholarship, write for broader audiences, and address inequities in knowledge production, dissemination, and consumption (cf Czerniewicz, 2013; Scharber et al., 2019). At a systemic level, we may question practices like top-tier publishing, rankings, impact factors, and the various practices that sustain and encourage these, such as institutional policies on promotion and advancement and grant-funding decisions.

A second possible response may involve reflecting on our own scholarship and the scholarship we support, reward, and encourage. Reeves and Lin (2020) argue that to make a real difference in the lives of learners we should be studying and solving problems, rather than studying tools and technologies. In effect, these authors urge us to ask whether our particular work, the work of our students, and the work of our colleagues contributes to better educational futures. My intent here is not to draw demarcation lines between appropriate and inappropriate scholarship. Instead, if higher education is facing the very real possibility that the post-pandemic era may be radically different than our earlier “normal” (Cox et al., 2020), this may be a good time to ask: What should the future of digital, online, and flexible education look like?

This is not a call for more hopeful writing of the possibilities of online education or educational technology. Instead, it is a call for more critical and speculative writing and practice. Such critical efforts are gaining broader visibility and interest and can be found in recent work in both this journal (e.g., Valcarlos et al., 2020) and elsewhere (e.g., Lambert, 2018). To imagine possible educational futures, some researchers are turning to speculative methods as “research approaches that explore and create possible futures under conditions of complexity and uncertainty” (Ross, 2018, p. 197). Envisioning such futures does not solely mean employing fiction in our writing. Rather, speculative methods “inform us about what matters now in the field, what issues and problems we have inherited, and what debates define what can or cannot be currently thought about or imagined” (Ross, 2017, p. 220). Considering that the current state of education, at all levels, is situated within a context of ever-evolving social, cultural, political, and technological shifts, we face an urgent need to engage with uncertainty on multiple levels.

The use of speculative methods, therefore, may enable us to offer guidance when making current decisions related to the future of higher education, and to explore what may or may not be possible in different contexts. In a special issue of Learning, Media and Technology (Selwyn et al., 2019) for example, colleagues examined near-future educational scenarios and critically contemplated the use of technology in education. To use an example of present activities to speculate about desirable and undesirable educational futures, consider the now-broader use of proctoring tools, which were largely adopted to maintain the continuity of such familiar practices as invigilated exams. Now consider a future in which proctoring tools are as pervasive as the use of learning management systems or even email. Are proctoring tools consistent with desirable future educational systems? Asking this question forces us to deal with the ethics of our work. What if, in the process of asking this question, we realize that adopting proctoring software may not only become a barrier to alternative assessments but may also foster a culture of surveillance and mistrust (e.g., Fawns & Ross, 2020; Swauger, 2020)?

Conclusion

Clearly, technology alone will be unable to provide a solution to such a complicated problem as responding to the complex challenges that educational systems worldwide are facing. The two possible responses I offer—broadening the reach and impact of our scholarship and engaging in more imaginative, speculative, and critical work—are not panaceas either. Unlike technological solutionism though, these actions respond to calls by Facer and Sanford (2010), Ross (2017), Staley (2019), and Alexander (2020) to develop scenarios for the future of higher education as a way to address current challenges and work toward desirable outcomes. I imagine such futures to be inclusive, equitable, and just; to serve all of our learners; to prioritize collaboration over competition; to be flexible to learners’ needs; to exhibit care and trust for our students; and to be free of systems of oppression and injustice that operate within our own institutions.

References

Alexander, B. (2020). Academia next: The futures of higher education . Johns Hopkins University Press. 

Bayne, S. (2015). What’s the matter with ‘technology-enhanced learning’? Learning, Media and Technology , 40(1), 5–20. 

Cox, R. , Slick, J. , & Dixon, T. (2020). Surviving, thriving, or radical revisioning: Scenarios and considerations for pandemic recovery and response planning . Royal Roads University. 

Czerniewicz, L. (2013, April 29). Inequitable power dynamics of global knowledge production and exchange must be confronted head on. Impact of Social Science. https://press.rebus.community/openatthemargins/chapter/repost-inequitable-power-knowledge/  

Facer, K. , & Sandford, R. (2010). The next 25 years? Future scenarios and future directions for education and technology. Journal of Computer Assisted Learning , 26(1), 74–93. 

Fawns, T. , & Ross, J. (2020, June 3). Spotlight on alternative assessment methods: Alternatives to exams. Teaching Matters . https://www.teaching-matters-blog.ed.ac.uk/spotlight-on-alternative-assessment-methods-alternatives-to-exams/  

Houlden, S. , & Veletsianos, G. (2020, March 13). COVID-19 pushes universities to switch to online classes—but are they ready? The Conversation. https://theconversation.com/covid-19-pushes-universities-to-switch-to-online-classes-but-are-they-ready-132728  

Lambert, S. R. (2018). Changing our (dis)course: A distinctive social justice aligned definition of open education. Journal of Learning for Development , 5(3), 225–244. https://jl4d.org/index.php/ejl4d/article/view/290/334  

Oliver, M. (2011). Technological determinism in educational technology research: some alternative ways of thinking about the relationship between learning and technology. Journal of Computer Assisted Learning , 27(5), 373–384.

Reeves, T. C. , & Lin, L. (2020). The research we have is not the research we need. Educational Technology Research and Development , 68(4), 1991–2001.

Ross, J. (2017). Speculative method in digital education research. Learning, Media and Technology , 42(2), 214–229.

Ross, J. , (2018). Speculative method as an approach to researching emerging educational issues and technologies. In L. Hamilton & J. Ravenscroft (Eds,), Building research design in education (pp. 197–212). Bloomsbury. 

Scharber, C. , Pazurek, A. , & Ouyang, F. (2019). Illuminating the (in)visibility of female scholars: A gendered analysis of publishing rates within educational technology journals from 2004 to 2015. Gender and Education , 31(1), 33–61.

Selwyn, N. (2011). In praise of pessimism—the need for negativity in educational technology. British Journal of Educational Technology , 42(5), 713–718.

Selwyn, N. , Hillman, T. , Eynon, R. , Ferreira, G. , Knox, J. , Macgilchrist, F. , & Sancho-Gil, J. M. (Eds.). (2019). Education and technology into the 2020s: Speculative futures [Special issue]. Learning, Media and Technology , 45(1). 

Staley, D. J. (2019). Alternative universities: Speculative design for innovation in higher education . Johns Hopkins University Press.  

Swauger, S. (2020). Our bodies encoded: Algorithmic test proctoring in higher education. In J. Stommel, C. Friend, & S. M. Morris (Eds.), Critical digital pedagogy: A collection. Pressbooks. https://cdpcollection.pressbooks.com/chapter/our-bodies-encoded-algorithmic-test-proctoring-in-higher-education/  

Tennyson, R. D. (1994). The big wrench vs. integrated approaches: The great media debate. Educational Technology Research and Development , 42(3), 15–28.

Valcarlos, M. M. , Wolgemuth, J. R. , Haraf, S. , & Fisk, N. (2020). Anti-oppressive pedagogies in online learning: A critical review. Distance Education , 41(3), 345–360. 

Watters, A. (2014). The monsters of education technology. Tech Gypsies Publishing. http://monsters.hackeducation.com   

Weller, M. (2020). 25 years of ed tech . Athabasca University Press.

CFP: Attending to Issues of Social Justice through Learning Design

The call for proposals below comes at an opportune time following the Scholar Strike action that occurred on September 8 and 9 both in the US and in Canada.

Journal of Applied Instructional Design Special Issue 2020 
“Attending to Issues of Social Justice through Learning Design” 


We specifically seek contributions from K-12, higher education, and other organizational or workplace contexts (e.g., non-profit organizations, government, corporate) that focus on how learning design can serve as a tool for pushing back against and/or changing systems that often promote or perpetuate injustice and inequality. Such work will likely deviate from more traditional instructional design and performance improvement approaches or improve upon them in some way to address topics that include but are not limited to:

  • Culturally-situated and cross-cultural approaches to instructional design and research
  • Improving performance in the context of workplace inequity
  • Participatory models of learning (e.g., Youth-led Participatory Action Research)
  • Long-term projects that address disparity issues regarding access to technologies and resources (e.g., digital and pedagogical divide)
  • Applications of critical theory in learning design
  • Ethical and responsible (i.e., humanizing) concerns regarding the collection, analysis, and presentation of data and findings

Deadline October 16, 2020. Complete details can be found here:
https://aect.org/news_manager.php?page=21693

10 interesting papers in the proceedings of the Artificial Intelligence in Education 2018 conference #aied18

The 2018 Artificial Intelligence in Education conference starts today. Its full proceedings are freely available online until July 21st, and I scrolled through them to identify papers/posters/reports that seemed potentially relevant to my work. These are of interest to me because some use methods that seem worthwhile, others offer insightful results, and yet others seem to make unsubstantiated claims.  As an aside, I especially like the fact that AIED offers space for PhD students to discuss their proposed research.

Here’s the papers that I identified to read:

Leveraging Educational Technology to Improve the Quality of Civil Discourse

Towards Combined Network and Text Analytics of Student Discourse in Online Discussions

An Instructional Factors Analysis of an Online Logical Fallacy Tutoring System

Adapting Learning Activities Selection in an Intelligent Tutoring System to Affect

Preliminary Evaluations of a Dialogue-Based Digital Tutor

ITADS: A Real-World Intelligent Tutor to Train Troubleshooting Skills

Early Identification of At-Risk Students Using Iterative Logistic Regression

Smart Learning Partner: An Interactive Robot for Education

Do Preschoolers ‘Game the System’? A Case Study of Children’s Intelligent (Mis)Use of a Teachable Agent Based Play-&-Learn Game in Mathematics

A Data-Driven Method for Helping Teachers Improve Feedback in Computer Programming Automated Tutors

 

 

Comment sentiment expressed in YouTube TED talk comments

The top definition of YouTube comments in the urban dictionary is the following: “the only place where a polite discussion about kittens can lead to a flame war about government conspiracies.”

Inquisitive readers might ask: Is that flame war the same for all videos? Or is it more likely for some videos than others?

Our latest paper (and when I write our, I am referring to Royce k=Kimmons, Tonia Dousay, Patrick Lowenthal, and Ross Larsen) explores whether the sentiment expressed toward scholars who go online varies according to variables of interest. Put differently, scholars are encouraged to be present online, to establish a digital identity, and expand their reach and impact. But, what is the public’s reaction? Does the public react more positively/negatively to some people? There’s many ways to go about exploring this question. We sought to answer this question by examining YouTube comments, but one could investigate tweets, blog comments, self-reported data, and so on. Below is our abstract, summarizing our findings, and link to our paper. Note the impact of gender, animations, and moderation on expressed sentiment:

 

Veletsianos, G., Kimmons, R., Larsen, R., Dousay, T., & Lowenthal, P. (2018). Public Comment Sentiment on Educational Videos: Understanding the Effects of Presenter Gender, Video Format, Threading, and Moderation on YouTube TED Talk Comments. PLOS ONE 13(6): e0197331. https://doi.org/10.1371/journal.pone.0197331

 

Scholars, educators, and students are increasingly encouraged to participate in online spaces. While the current literature highlights the potential positive outcomes of such participation, little research exists on the sentiment that these individuals may face online and on the factors that may lead some people to face different types of sentiment than others. To investigate these issues, we examined the strength of positive and negative sentiment expressed in response to TEDx and TED-Ed talks posted on YouTube (n = 655), the effect of several variables on comment and reply sentiment (n = 774,939), and the projected effects that sentiment-based moderation would have had on posted content. We found that most comments and replies were neutral in nature and some topics were more likely than others to elicit positive or negative sentiment. Videos of male presenters showed greater neutrality, while videos of female presenters saw significantly greater positive and negative polarity in replies. Animations neutralized both the negativity and positivity of replies at a very high rate. Gender and video format influenced the sentiment of replies and not just the initial comments that were directed toward the video. Finally, we found that using sentiment as a way to moderate offensive content would have a significant effect on non-offensive content. These findings have far-reaching implications for social media platforms and for those who encourage or prepare students and scholars to participate online.

Educational Technology Magazine archive (1966-2017)

Larry Lipsitz, the founder and long-time editor of Educational Technology magazine, passed away last year and is missed by many (see the tributes and remembrances many of us wrote in the last issue of the magazine).

With Larry’s insight, Educational Technology published cutting-edge, critical, thoughtful, and important work.

Educational Technology was a print-only publication. However, Howard Lipsitz, Larry’s brother, has collaborated with JSTOR to preserve Larry’s legacy and make all articles available online where they can be read for free. Here’s the Educational Technology magazine archives (1966-2017).

 

 

Imagine a future in which technologies teach humans

Pause for a few minutes and imagine a future in which technologies teach humans. Call them robots, bots, chatbots, algorithms, teaching machines, tutoring software, agents, or something else. Regardless, consider them technologies that teach.

robo_teacher

Vector created by Freepik

How far into the future is that time?

What do these technologies look like? Are they anthropomorphous? Are they human-like? In what ways are they human-like? Do they have voice capabilities, and if so, do they understand natural language? Are they men or women?  Do they have a representation in the way that one would imagine a teacher – such as a pedagogical agent – or do they function behind the scenes in ways that seem rather innocuous – such as the Mechanical MOOC?

Do these technologies teach humans of all ages? Do they teach independently, support human teachers, or do human teachers assist them? Are they featured in articles in the New York Times, The Guardian, and The Economist as innovations in education? Or, are they as common as desks and chairs, and therefore of less interest to the likes of the New York Times? Are they common in all learning contexts? Who benefits from technologies that teach? Is being taught by these technologies better or worse than being taught be a human teacher? In what ways is it better or worse? Are they integrated in affluent universities and k-12 schools? Or, are they solely used in educational institutions serving students of low socioeconomic status? Who has access to the human teachers and who gets the machines? Are they mostly used in public or private schools?

How do learners feel about them? Do they like them? Do they trust them? Ho do learners think that these technologies feel about them? Do they feel cared for and respected? How do learners interact with them? How do human teachers feel about them? Would parents want their children to be taught be these technologies? Which parents have a choice and which parents don’t? How do politicians feel about them? How do educational technology and data mining companies view them?

Do teaching technologies treat everyone the same based on some predetermined algorithm? Or, are their actions and responses based on machine learning algorithms that are so complex that even the designers of these technologies cannot predict their behaviour with exact precision? Do they subscribe to pre-determined pedagogical models? Or, do they “learn” what works over time for certain people, in certain settings, for certain content areas, for certain times of the day? Do they work independently in their own classroom? Or, do colonies of robo-teachers gather, share, and analyze the minutiae of student life, with each robo-teacher carefully orchestrating his or her next evidence-based pedagogical move supported by Petabytes of data?

Final question for this complicated future, I promise: What aspects of this future are necessary and desirable, and why?

Page 2 of 6

Powered by WordPress & Theme by Anders Norén