Tag: ETEC 511

Introduction

By way of the COVID-19 pandemic, global health has dictated when, where, and how people work and learn. Educational technologies tools quickly leaned upon for maintaining a sense of normalcy in an otherwise chaotic existence. In the span of only a few months, 50% of in-person training in North America was cancelled while 100% were cancelled in some parts of Europe and Asia (Kshirsagar et al., 2020). Even after front-line workers returned to in-person work, 40% of Canadians remained working from home (Mehdi & Morissette, 2021). Online video conferencing platforms were used to maintain connections between students and employees alike and Zoom saw its worldwide webinar minutes jump from 3 billion to 45 billion in span of 6 months (Dean, 2022).

As responsible as COVID-19 is for ‘revolutionizing’ schools and workplaces and expediting access to remote options (Robinson, 2022), evidence already existed showing the interconnectedness between technology and global health:

“The rapid increase in speed of travel and communication, as well as the economic interdependency of all nations, has led to a new level and speed of global interconnectedness or globalisation, which is a force in shaping the health of populations around the world” (Koplan et al., 2009, p. 1994).

However, the pandemic also highlighted key characteristics for global health: transcending national boarders, global cooperation, and valuing interdisciplinary and multidisciplinary teams (Koplan et al., 2009). In these ways, global health is, and will continue to, influence how we use learning technologies.

Transcending National Boarders

Suddenly, the ‘entire world’ (or how it was made to seem) was working and learning online. This reminded all global inhabitants of our interconnectedness, not just by being human but also through the physical internet cables running across ocean floors (Hammel & Yurshansky, 2016). Our shared global health experiences were driving the requirement of new knowledge, as digital upskilling and reskilling emerged as the most pressing learning concerns in workplaces around the world (OECD, 2020).

While the global health situation dictated skill development, skill development in turn supports global health. Skill diversification can improve health outcomes, life expectancy, child vaccination rates, and overall well-being (Raghupathi & Raghupathi, 2020). Building digital skills also promotes lifelong learning, thus increasing skills for employment, continued education, and global citizenship (COVIDEA, 2020).

However, it is important to note that some aspects of technology do not transcend national boarders. Using eLearning sector data, 70% of eLearning activity takes place in North America and Europe (Khan, 2022). Only one-tenth of workers in India can work remotely, compared to 40% of workers in advanced economic countries (Rajadhyaksha, 2021). Similarly, in developing countries, investments in technology often go unused because teachers are not provided with digital training to operate them (Dercon, 2019). In order for learning technologies to integrate more solidly with the skills-lead-to-improved-health-outcomes approach, the approach much be two-fold: provide the hardware, and also promote the “system-wide connections enabled by digital technology” (Dercon, 2019, para. 4).

Global Cooperation

Technology is also connected to global health as we consider the “well-being of both people and planet” (course notes, module 5). As learning technology around the world increased, air quality also increased (Venter et al., 2020). Moving to digital communications instead of international travel once again showed us that major issues transcend borders but that many solutions to current health issues require global cooperation.

Technology was also used to provide ‘telehealth’ options. Virtual connections to hospitals and doctors yielded a 75% satisfaction rate among telehealth patients, and telehealth usage was 38-times higher than pre-pandemic rates (Bestsennyy et al., 2021). As people were forced to use these technologies to learn and communicate about their health, attitudes toward the technology improved, making it far more likely to continue as an option.

Interdisciplinary and Multidisciplinary Teams

In a 2022 Workplace Learning Report, learning and development professionals cited becoming more cross-functional with teams like diversity, equity and inclusion, and people analytics (LinkedIn, 2022). Analytics, particularly, represents the value of interdisciplinary work, and both predictive and advanced analytics can help learning via technologies become more engaging, quantifiable, and transformational (LinkedIn, 2022). The value of using data in educational technologies echoes the importance of data for global health, as witnessed through dedicated COVID-19 pandemic data sites (Ritchie et al., 2020).

Conclusion

When considering the aspects of transcending national borders, fostering global cooperation, and encouraging interdisciplinary teams, there are many parallels between global health and technology. These two realms have been feeding into each other for the duration of the recent pandemic, only for both to emerge even more dependent on each other. It will be impossible to see technology try to extricate itself from the impact it has on global health, and the opposite is also true. Of the many lessons learned during this pandemic, one that will not be soon forgotten is that of the interconnectedness of global health and educational technologies.

References

Bestsennyy, O., Gilbert, G., Harris, A., & Rost, J. (2021, July 9). Telehealth: A quarter-trillion-dollar post-COVID-19 reality? McKinsey & Company. https://www.mckinsey.com/industries/healthcare-systems-and-services/our-insights/telehealth-a-quarter-trillion-dollar-post-covid-19-reality

COVID EDUCATION ALLIANCE (COVIDEA). (2020 October). Adapting education systems to a fast changing and increasingly digital world through the use of appropriate technologies: A Primer. Foundation for Global Governance and Sustainability (FOGGS). https://www.foggs.org/wp-content/uploads/2020/10/COVIDEA-Primer_FINAL_October2020-2.pdf

Dean, B. (2022, January 6). Zoom user stats: How many people use Zoom in 2022? Backlinko. https://backlinko.com/zoom-users

Dercon, S. (2019, May 31). Is technology key to improving global health and education, or just an expensive distraction? World Economic Forum. https://www.weforum.org/agenda/2019/05/technology-health-education-developing-countries/

Hammel, N. & Yurshansky, L. (Nat and Friends). (2016, December 16). A journey to the bottom of the internet [Video]. YouTube. https://www.youtube.com/watch?v=H9R4tznCNB0

Khan, M. J. (2022, January 20). Facts and stats that reveal the power of the eLearning sector. eLearning Industry. https://elearningindustry.com/facts-and-stats-that-reveal-the-power-of-the-elearning-sector

Koplan, J. P., Bond, T. C., Merson, M. H., Reddy, K. S., Rodriguez, M. H., Sewankambo, N. K., & Wasserheit, J. N. (2009). Towards a common definition of global health. The Lancet, 373(9679), pp. 1993-1995. https://doi.org/10.1016/S0140-6736(09)60332-9a

Kshirsagar, A., Mansour, T., McNally, L., & Metakis, M. (2020, March 17). Adapting workplace learning in the time of coronavirus. McKinsey & Company. https://www.mckinsey.com/business-functions/people-and-organizational-performance/our-insights/adapting-workplace-learning-in-the-time-of-coronavirus

LinkedIn Learning. (2022). 2022 workplace learning report: The transformation of L&D. https://learning.linkedin.com/resources/workplace-learning-report#2 and https://learning.linkedin.com/content/dam/me/learning/en-us/pdfs/workplace-learning-report/LinkedIn-Learning_Workplace-Learning-Report-2022-EN.pdf

Mehdi, T. & Morissette, R. (2021, October 27). Working from home in Canada: What have we learned so far? Statistics Canada. https://doi.org/10.25318/36280001202101000001-eng

Organisation for Economic Co-operation and Development (OECD). (2020, July 24). The potential of online learning for adults: Early lessons from the COVID-19 crisis. https://www.oecd.org/coronavirus/policy-responses/the-potential-of-online-learning-for-adults-early-lessons-from-the-covid-19-crisis-ee040002/

Picheta, R. (2020, April 9). People in India can see the Himalayas for the first time in ‘decades,’ as the lockdown eases air pollution. CNN Travel. https://www.cnn.com/travel/article/himalayas-visible-lockdown-india-scli-intl/index.html

Raghupathi, V. & Raghupathi, W. (2020). The influence of education on health: an empirical assessment of OECD countries for the period 1995-2015. Arch Public Health, 78(20). https://doi.org/10.1186/s13690-020-00402-5

Rajadhyaksha, N. (2021, May 5). The new Zoom economy: Who can adjust to it and who cannot? Mint. https://www.livemint.com/opinion/columns/the-new-zoom-economy-who-can-adjust-to-it-and-who-cannot-11620153630824.html

Ritchie, H., Mathieu, E., Rodés-Guirao, L., Appel, C., Giattino, C., Ortiz-Ospina, E., Hasell, J., Macdonald, B., Beltekian, D. & Roser, M. (2020). Coronavirus Pandemic (COVID-19). OurWorldInData.org. https://ourworldindata.org/coronavirus

Robinson, B. (2022, February 1). Remote work is here to stay and will increase into 2023, experts say. Forbes.
https://www.forbes.com/sites/bryanrobinson/2022/02/01/remote-work-is-here-to-stay-and-will-increase-into-2023-experts-say/?sh=6a3e6ce920a6

Venter, Z. S., Aunan, K., Chowdhury, S., & Lelieveld, J. (2020). COVID-19 lockdowns cause global air pollution declines. PNAS, 117(32). https://doi.org/10.1073/pnas.2006853117

Project

Canadian Curriculum Corner (Danika, Nicki, & Melissa)

Project Design/Development

We first considered our interests/professional audiences:  K-12 teachers, post-secondary students, and adults. BC’s curriculum had recently been updated, and their new approach appealed to us on all fronts. We realized that curriculum was mostly presented as massive, text-based PDFs. Even teachers who knew what to look for had a hard time finding the information quickly, let alone parents wanting to support their students, college/university administrators trying to support incoming students, or the eager K-12 student curious to investigate their learning objectives (I’m sure they exist…somewhere). Additionally, the inconsistencies between provinces and territories was dizzying; we determined that provincial and territorial curriculum differences should be honoured, but it would be nice to have one place to check their differences and similarities. Also, wouldn’t it be nice if people got excited to read curriculum?!

We kept reminding ourselves of Issa & Isaias’s (2015) usability criteria, particularly section 2.4.2, and let this guide us. We asked ourselves questions like, “how are the current formats low in usability criteria, and in what ways can we improve user experience?” In order to answer that for our users, we defined them: teachers obviously needed access to curriculum, and likely at the deepest level of detail; parents would want a high-level summary, perhaps with some connection to future skills; and students would want to know why they should care. We discussed the differences between our audiences and determined that a website was best to present this tool.

After collaborating on the proposal, we divided the work based on our interests and skills. I took on the provincial and territorial website reviews, citing usability elements. The diverse range was fascinating, especially as an ‘outsider’ (aka, not K-12 teacher) trying to access and understand the curriculum. This provided insight from a usability perspective and determined the importance of creating a website with targeted audience information, clear navigation, and engaging design. While assessing websites, my notes naturally fell into four of Issa & Isaias’s (2015) usability criteria: learnability (could I find what I was looking for?), flexibility (could I access the information a few different ways?), efficiency (how many clicks did it take me to get there?), and satisfaction (did I enjoy the website?). From here, the comparison chart was born. Additionally, I researched website best practices, particularly around usability. Next, I started drafting the website figuring out how best to present our information. This took some trial and error but, again, our own trials provided valuable information.

Our process and product went well. I wish we’d had more time, or energy (or both), to work on this, as it was a slow realization of how massive this was. We trimmed content and pivoted a few times, but are quite happy with how it came together. After listening to other groups, I wish we had presented it to some teachers, parents, and students to gather their feedback. Feedback gathered after the fact has been good so far, though: “this is really easy to navigate. Looks good.”

(Tip: make the Genially full screen by clicking the two opposing arrows in the bottom right corner. There will be a button in the same spot to shrink it back down when you’re done.)

 

References

Abbott, T. (2022, April 25). How much data does a Zoom meeting use? Reviews.org. https://www.reviews.org/internet-service/how-much-data-does-zoom-use/

Bartel, A. P., & Sicherman, N. (1993). Technological Change and Retirement Decisions of Older Workers. Journal of Labor Economics, 11(1), pp. 162–183. http://www.jstor.org/stable/2535188

Benefits Canada. (2022, March 10). 80% of U.S. workers experiencing ‘Zoom fatigue:’ survey. https://www.benefitscanada.com/benefits/health-wellness/80-of-u-s-workers-experiencing-zoom-fatigue-survey/

Dean, B. (2022, January 6). Zoom user stats: How many people use Zoom in 2022? Backlinko. https://backlinko.com/zoom-users

Forrester. (2022, February). The total economic impact of Zoom’s unified communications platform. https://explore.zoom.us/media/zoom-ucaas-total-economic-impact-2022.pdf

Gajendran, R. S., & Harrison. D. A. (2007). The good, the bad, and the unknown about telecommuting: Meta-analysis of psychological mediators and individual consequences. Journal of Applied Psychology, 92, 6, 1524-1541. https://doi.org/10.1037/0021-9010.92.6.1524

Harter, J. & Mann, A. (2017, April 12). The right culture: Not just about employee satisfaction. Gallup.  https://www.gallup.com/workplace/236366/right-culture-not-employee-satisfaction.aspx

McLeod, S. (updated 2022, April 4). Maslow’s hierarchy of needs. Simply Psychology. https://www.simplypsychology.org/maslow.html

Morgan, J. (2022, June 3). How much time do you spend in virtual meetings? LinkedIn. https://www.linkedin.com/pulse/how-much-time-do-you-spend-virtual-meetings-jacob-morgan/

Obringer, R., Rachunok, B., Maia-Silva, D. M., Arbabzadeh, M., Nateghi, R.,  & Madani, K. (2021). The overlooked environmental footprint of increasing Internet use. Resources, Conservation and Recycling, 167. https://doi.org/10.1016/j.resconrec.2020.105389

Perna, M. C. (2022, February 1). Why it’s time to shatter the Zoom ceiling and embrace remote work. Forbes. https://www.forbes.com/sites/markcperna/2022/02/01/why-its-time-to-shatter-the-zoom-ceiling-and-embrace-remote-work/?sh=35fd66006927

Rajadhyaksha, N. (2021, May 5). The new Zoom economy: Who can adjust to it and who cannot? Mint. https://www.livemint.com/opinion/columns/the-new-zoom-economy-who-can-adjust-to-it-and-who-cannot-11620153630824.html

Ramachandran, V. (2021, February 23). Stanford researchers identify four causes for ‘Zoom fatigue’ and their simple fixes. Stanford News. https://news.stanford.edu/2021/02/23/four-causes-zoom-fatigue-solutions/

Ranger, S. (2022, August 9). Malcolm Gladwell says working from home is ‘not in your best interests.’ The reality is much more complicated. ZDNet. https://www.zdnet.com/article/malcom-gladwell-says-working-from-home-is-not-in-your-best-interests-its-much-more-complicated-than-that/

Robinson, B. (2021, October 15). Remote workers report negative mental health impacts, new study finds. Forbes. https://www.forbes.com/sites/bryanrobinson/2021/10/15/remote-workers-report-negative-mental-health-impacts-new-study-finds/?sh=3eed3cdb74b8

Sklar, J. (2020, April 24). ‘Zoom fatigue’ is taxing the brain. Here’s why that happens. National Geographic. https://www.nationalgeographic.com/science/article/coronavirus-zoom-fatigue-is-taxing-the-brain-here-is-why-that-happens

Tu , M. & Li, M. (2021, May 12). What great mentorship looks like in a hybrid workplace. Harvard Business Review. https://hbr.org/2021/05/what-great-mentorship-looks-like-in-a-hybrid-workplace

Venter, Z. S., Aunan, K., Chowdhury, S., & Lelieveld, J. (2020, July 28). COVID-19 lockdowns cause global air pollution declines. PNAS, 117 (32), pp. 18984-18990. https://doi.org/10.1073/pnas.2006853117

Wilson, J. (2021, April 22). Is Zoom fatigue worse for women? Canadian HRReporter. https://www.hrreporter.com/focus-areas/wellness-mental-health/is-zoom-fatigue-worse-for-women/355238

Wolf, C. R. (2020, May 14). Virtual platforms are helpful tools but can add to our stress. Psychology Today. https://www.psychologytoday.com/us/blog/the-desk-the-mental-health-lawyer/202005/virtual-platforms-are-helpful-tools-can-add-our-stress

Yashiro, N. , Kyyra, T., Hwang, H., & Tuomala, J. (2021, October). Technology, labour market institutions and early retirement. Economic Policy. https://www.economic-policy.org/wp-content/uploads/2021/10/9104_Yashiro_etal.pdf

 

Tipping Point: Video Conferencing Tools (e.g., Zoom) and Global Health

Submitted by Melissa Santo and Alice Shin

Initial Proposal

This case study will consider global health as a facilitator in the displacement of primarily in-person workplaces and corporate training to fully remote or hybridized work environments due to the widespread use of video conferencing (e.g., Zoom). 

This displacement was due to the COVID-19 pandemic which began early in 2020, triggering a global lockdown to prevent the spread of the disease. As phone calls, texting, and emails were clearly impractical for businesses to operate, workplaces adopted video conferencing as this tool created the closest thing to immediate in-person contact. Video conferencing allowed learning to continue via one-to-one and group training sessions, presentations, and workshops, along with various HR-related training activities such as employee onboarding. This technology also supported professional development which assisted in maintaining morale, building worker resilience, and supporting overall employee mental health.

Final Product: Powtoon presentation (posted to YouTube)

Note: the free version of Powtoon limits all videos to 3 minutes. 

References

Anderson, S. & Euronews. (2020, April 3). Coronavirus: Half of humanity now on lockdown as 90 countries call for confinement. https://www.euronews.com/2020/04/02/coronavirus-in-europe-spain-s-death-toll-hits-10-000-after-record-950-new-deaths-in-24-hou 

Carter, E. (2020, November 12). We could get used to this: Americans embrace remote work. Morning Brew. https://www.morningbrew.com/daily/stories/2020/11/12/get-used-americans-embrace-remote-work-per-exclusive-morning-brew-polling

Chang, A. (2020, November 12). Work from home perks will outlast COVID-19. What this means. The San Diego Union Tribune. https://www.sandiegouniontribune.com/business/technology/story/2020-11-12/companies-will-allow-employees-to-work-wherever-they-want 

Dean, B. (2022, January 6). Zoom user stats: How many people use Zoom in 2022? Backlinko. https://backlinko.com/zoom-users 

Demiraj, G.  (2021, January 19). The Covid -19 Pandemic Brok Corporate Training – It’s a good thing. The Training Industry. https://trainingindustry.com/articles/content-development/the-covid-19-pandemic-broke-corporate-training-which-is-a-good-thing/ 

Fox, D. (2021, April 5). Remote Learning: How remote work made corporate learning work better. NovoEd. https://www.novoed.com/resources/blog/one-year-on-how-remote-work-made-corporate-learning-work-better/ 

Gajendran, R. S., & Harrison. D. A. (2007). The good, the bad, and the unknown about telecommuting: Meta-analysis of psychological mediators and individual consequences. Journal of Applied Psychology, 92, 6, 1524-1541. https://doi.org/10.1037/0021-9010.92.6.1524 

Green, S. (2022, January 20). The big 5 learning delivery methods for companies. iSpring. https://www.ispringsolutions.com/blog/learning-delivery-methods 

Harter, J. & Mann, A. (2017, April 12). The right culture: Not just about employee satisfaction. Gallup.  https://www.gallup.com/workplace/236366/right-culture-not-employee-satisfaction.aspx 

Kaushik, K. How employee engagement drives productivity of remote workers. Apty. https://www.apty.io/blog/how-employee-engagement-drives-productivity-of-remote-workers

Kshirsagar, A., Mansour, T., McNally, L., & Metakis, M. (2020, March 17). Adapting workplace learning in the time of coronavirus. McKinsey & Company. https://www.mckinsey.com/business-functions/people-and-organizational-performance/our-insights/adapting-workplace-learning-in-the-time-of-coronavirus 

LinkedIn Learning. (2022). 2022 workplace learning report: The transformation of L&D. https://learning.linkedin.com/resources/workplace-learning-report#2 and https://learning.linkedin.com/content/dam/me/learning/en-us/pdfs/workplace-learning-report/LinkedIn-Learning_Workplace-Learning-Report-2022-EN.pdf

Lund, S., Madgavkar, A., Manyika, J., Smit, S., Ellingrud, K., & Robinson, O. (2021, February 18). The future of work after COVID-19. McKinsey Global Institute. https://www.mckinsey.com/featured-insights/future-of-work/the-future-of-work-after-covid-19 

Mehdi, T. & Morissette, R. (2021, October 27). Working from home in Canada: What have we learned so far? Statistics Canada. https://doi.org/10.25318/36280001202101000001-eng 

Oakman, J., Kinsman, N., Stuckey, R., Graham, M., & Weale, V. (2020). A rapid review of mental and physical health effects of working at home: How do we optimise health? BCM Public Health, 20, 1825. https://doi.org/10.1186/s12889-020-09875-z 

Organisation for Economic Co-operation and Development (OECD). (2020, July 24). The potential of online learning for adults: Early lessons from the COVID-19 crisis. https://www.oecd.org/coronavirus/policy-responses/the-potential-of-online-learning-for-adults-early-lessons-from-the-covid-19-crisis-ee040002/ 

Raghupathi, V. & Raghupathi, W. (2020). The influence of education on health: an empirical assessment of OECD countries for the period 1995-2015. Arch Public Health, 78, 20. https://doi.org/10.1186/s13690-020-00402-5 

Robinson, B. (2021, October 15). Remote workers report negative mental health impacts, new study finds. Forbes. https://www.forbes.com/sites/bryanrobinson/2021/10/15/remote-workers-report-negative-mental-health-impacts-new-study-finds/?sh=3eed3cdb74b8

Robinson, B. (2022, February 1). Remote work is here to stay and will increase into 2023, experts say. Forbes. https://www.forbes.com/sites/bryanrobinson/2022/02/01/remote-work-is-here-to-stay-and-will-increase-into-2023-experts-say/?sh=6a3e6ce920a6

Venter, Z. S., Aunan, K., Chowdhury, S., & Lelieveld, J. (2020). COVID-19 lockdowns cause global air pollution declines. PNAS, 117, 32.  https://doi.org/10.1073/pnas.2006853117 

Vogel, L. & Eggertson, L. (2020, June 12). COVID-19: A timeline of Canada’s first-wave response. CMAJ News. https://cmajnews.com/2020/06/12/coronavirus-1095847/ 

Wolfe, B. (2021, September 13). 54% of Canadian employers adopting hybrid work, meeting employee expectations: Survey. Benefits Canada. https://www.benefitscanada.com/human-resources/hr-communication/54-of-canadian-employers-adopting-hybrid-work-meeting-employee-expectations-survey/ 

Who were these people, and how did/does each contribute to the development of artificial intelligence? How did/does each think “intelligence” could be identified? (50 words each)

Alan Turing, a British mathematician and a ‘founding father’ of artificial intelligence (AI), proposed that humans solved problems and made decisions by applying reason to the information available to them (Anyoha, 2017). He believed that machines could show ‘thinking’ by mimicking the human process and that machine learning could occur by following “the normal teaching of a child” (Turing, 1950, p.22).

Building on this, John McCarthy, a computer and cognitive scientist, added that understanding how humans think was key to unlocking how to build problem-solving machines, but that AI goes beyond simulating human intelligence (“John McCarthy,” 2022). He sparked debate by claiming that AI means machines have ‘beliefs,’ referring to their ability to solve problems using question-answering and ‘if-then’ logic programming.

Herb Simon, a political scientist, connected AI to how humans make decisions, showing that they start with information and then follow a series of rules and used information processing languages to create logic and problem-solving machines (“Herbert A. Simon,” 2022). Simon highlighted that AI differed from human intelligence, as the latter still functions, albeit inconsistently, despite knowledge gaps and preferences (UBS Nobel Perspectives, n.d.).

Marvin Minsky, a mathematician and computer scientist, expanded ‘intelligence’ from procedural thinking to the result of several non-intelligent parts working together, creating the first artificial neural network (“Marvin Minsky,” 2022). Although critical of previous theories on human brain function, Minsky believed brains were machines that computers could copy. He believed AI would lead to machines outperforming people and strongly advised thorough testing (BBC News, 2016).

Timnit Gebru, a computer scientist, continued to highlight similarities between brains and machines, flagging flaws with AI like bias, racism, and ethical issues (“Timnit Gebru,” 2022). Gebru’s work emphasizes the need for representation not just in AI data and the individuals researching it but also to break down the systemic barriers within corporations that prevent diversity at all levels (Levy, 2021).

How do “machine (programming) languages” differ from human (natural) ones? (100 words)

Despite their similarities, machine/programming languages and human ones have notable differences. Programming languages are artificial creations where context is bound by pre-set rules (Harris, 2018). AI may ‘learn’ but it lacks morphology, the idea that word meaning can change based on context. Furthermore, human languages incorporate additional cues beyond simply words (body language, intonation, punctuation) to convey emotion and can use context to understand the meaning even when the words are unclear (mispronunciations), whereas programming language must be logical and precise. As Harris (2018) eluded, imperfections mean the code will not run while many humans possess the powerful ability to interpret and adapt.

How does “machine (artificial) intelligence” differ from the human version? (100 words)

Intelligence, according to McCarthy (2007), is the ability to achieve goals by means of processing information. AI is created with hard-coded rules, from which it cannot deviate, and operates within the confines of the designer’s understanding of a process at one specific time (Chollet, 2019; McCarthy, 2007). This makes AI excellent for collecting and managing massive data sets, processing data according to pre-set parameters, and completing tasks (Chollet, 2019). Human intelligence, however, is better able to generalize, adjust to nuances, and incorporate subtle changes in information like skin tone or cultural norms (Chollet, 2019; Hao, 2020; McCarthy, 2007). AI, therefore, is more about manipulating information and human intelligence is about trying to understand information (Hao, 2020).

How does “machine learning” differ from human learning? (100 words)

Machine learning is designed to make predictions about new information using coded datasets and algorithms (Heilweil, 2020). Unfortunately, when datasets are incomplete, which most are, it produces biased algorithms: varying accuracy rates and/or different decisions for different demographics such as sex, gender, and race (Buolamwini, 2019; Cirillo et al., 2020). These biases can result in “neglect[ing] desired differentiations…or amplify[ing] undesired ones” (Cirillo et al., 2020, para.58) that continue to promote inequalities and racism in systems governing human lives like education, recruitment, policing, and healthcare (Buolamwini, 2019; Cirillo et al., 2020; Heilweil, 2020). While humans are also biased, they often possess the flexibility to adapt to changing contexts and objective scenarios, which is not a feature of machine learning (Heilweil, 2020).

And for your LAST challenge, a version of the Turing Test: how do YOUR answers to these questions differ from what a machine could generate? (200 words)

One of the first indicators that this was written by a human versus a machine is the (attempt) to connect the biography snippets in question 1. Words and phrases like “Building on this,” “expanded” and “continued” refer to the progress of AI in the context of information already included in the text on these specific people, not necessarily on the information on them found online. An article in Futurism suggested that acronyms and punctuation, like hyphens or apostrophes, can indicate human-generated content (Robitzski, 2019). In that light, the use of single apostrophes to imply additional context to terms understood by humans suggests a human author (e.g., “‘beliefs,’” “‘intelligence,’” and “‘learn’”). For fun, a sample from the above text was entered into a Giant Language model Test Room [http://gltr.io/dist/index.html] that highlighted several instances where the likelihood of a machine using that word was 1/1000 or less. These included adjectives (e.g., “notable differences” and “powerful ability”) and the word “morphology.” Another example is the use of the word “unfortunately,” which is included to convey an opinion. These examples suggest that this text is trying to represent emotion and a deeper connection between concepts, which are more characteristic of human intelligence (Hao, 2020).

References

Anyoha, R. (2017, August 28). The history of artificial intelligence. Harvard University. https://sitn.hms.harvard.edu/flash/2017/history-artificial-intelligence/

BBC News. (2016, January 26). AI pioneer Marvin Minsky dies aged 88. https://www.bbc.com/news/technology-35409119

Buolamwini, J. (2019, February 7). Artificial intelligence has a problem with gender and racial bias. Here’s how to solve it. Time. https://time.com/5520558/artificial-intelligence-racial-gender-bias/

Cirillo, D., Catuara-Solarz, S., Morey, C., Guney, E., Subirats, L., Mellino, S., Gigante, A., Valencia, A., Jose Rementeria, M., Santuccione Chadha, A., & Mavridis, N. (2020). Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare. npj Digital Medicine 3, 81. https://doi.org/10.1038/s41746-020-0288-5

Hao, K. (2020, December 4). We read the paper that forced Timnit Gebru out of Google. Here’s what it says. MIT Technology Review. https://www.technologyreview.com/2020/12/04/1013294/google-ai-ethics-research-paper-forced-out-timnit-gebru/

Harris, A. (2018, November 1). Human languages vs. programming languages. Medium. https://medium.com/@anaharris/human-languages-vs-programming-languages-c89410f13252

Herbert A. Simon. (2022, June 2). In Wikipedia. Retrieved June 5, 2022, from https://en.wikipedia.org/wiki/Herbert_A._Simon

John McCarthy (computer scientist). (2022, May 23). In Wikipedia. Retrieved June 5, 2022, from https://en.wikipedia.org/wiki/John_McCarthy_(computer_scientist)

Levy, M. G. (2021, November 9). Timnit Gebru says artificial intelligence needs to slow down. WIRED. https://www.wired.com/story/rewired-2021-timnit-gebru/

Marvin Minsky. (2022, May 25). In Wikipedia. Retrieved June 5, 2022, from https://en.wikipedia.org/wiki/Marvin_Minsky

McCarthy, J. (2007, November 12). What is artificial intelligence? Basic questions. Standford University. http://www-formal.stanford.edu/jmc/whatisai/node1.html

Robitzski, D. (2019, March 11). This site detects whether text was written by a bot. Futurism. https://futurism.com/detects-text-written-bot

Timnit Gebru. (2022, June 5). In Wikipedia. Retrieved June 5, 2022, from https://en.wikipedia.org/wiki/Timnit_Gebru

Turing, A. M. (1950). Computing machinery and intelligence. Mind, 49, 433-460. https://www.csee.umbc.edu/courses/471/papers/turing.pdf

UBS Nobel Perspectives. (n.d.). Herbert A. Simon: Nobel 1978 – Do we understand human behavior? https://www.ubs.com/microsites/nobel-perspectives/en/laureates/herbert-simon.html

Usability describes a collection of attributes that makes a system simple, intuitive, and efficient to users. It quantifies and qualifies the users’ experiences when interacting with systems to accomplish tasks. Issa and Isaias (2015) highlight that usability is multifaceted and encompasses many concepts. Its framework considers how systems function and the characteristics of both users and tasks, which collectively influence the user’s reaction. Usability assesses the intention behind and experience of the interaction, in addition to the accuracy of output, indicating whether the context and language between users and systems are in sync. High usability can lead to increased use, task retention, and decreased learning time. These advantages produce loyalty and profit. Usability can be misjudged in contexts where the intent of Human Computer Interaction (HCI) is to anticipate users’ future needs beyond current ones. As such, utility – or the anticipated function of a system – also plays a critical role in the perception of usability. This is particularly important in the context of education, as successful knowledge transfer often relies on purposeful problem-based learning where users understand why they are learning, particularly as adults. If the system produces results that are disjointed from what the user anticipates, it risks being assigned low usability and rejected.

Considering educational usability, one aspect that Issa and Isaias (2015) neglect to include is the social influence on learning. These include collaboration, cooperation, mentorship, feedback, and support from more knowledgeable others. Social Cognitive Theory emphasizes that learning takes place in social contexts, and therefore social influences can alter a user’s characteristics (knowledge, motivation, and discretion) significantly while being completely independent of them. For example, imagine an individual who has chosen to use an iPhone for the last decade. Recently, they started working for a new company that provides Android devices to all employees. In this case, negative outcomes of usability cannot lead to “suspension and discontinuation of the system” (Issa & Isaias, 2015, p.32) as it is a requirement for the new job. One could argue that this is simply motivation (learn new system = keep new job), however, that oversimplification neglects the value of social influence within the workplace. There is a profound divide between Android users and iPhone users, and one’s choice to engage with one or the other often goes beyond mere usability and relies more on the social constructs within which they see themselves. Marketing of technology and systems frequently capitalizes on social influence.

Woolgar (1990) alludes to these social influences in explaining the concept of configuring users. One example of users being configured in Woolgar’s (1990) account of the trials is the initial setup, designed to emulate an ordinary work environment. This creates an expectation of competence (I am successful at my job, so I can do this) while the features that are not often present at work, e.g., video cameras and observers, encourage users to persevere (they are watching so I will keep trying to make this work). Combined, these social aspects of the environment made the users think they were fit for any tasks presented in the trial.

A second example of configuring users was the commentary from the not-so-objective observers. Feedback like “you’ve done fine so far” or “let’s assume we succeeded there which I think you did” (Woolgar, 1990, p.85) can adjust the user’s perception of what occurred during the interaction. Here, the social influence collides with constructivism; the user’s reflective observation of their concrete experiences is being influenced and formed into a positive memory, thereby inflating the perceived usability of the technology.

One of the biggest differences between how Woolgar (1990) and Issa and Isaias (2015) present usability is their acknowledgement of what can, or should, be configured. Woolgar (1990) explicitly states that configuring users is a natural part of usability; by shaping and arranging users and their expectations they can be successfully set up for designated tasks, resulting in high usability. In contrast, Issa and Isaias (2015) imply that systems should be configured through iterations targeted to increase usability. The question then becomes, are these ever truly separate? Changes to a system will alter how users interpret and interact with it, thereby adjusting user reactions. Feedback and other steps taken to prepare and guide targeted users can make them fit better with the systems and tasks, swaying user characteristics and reactions. Ultimately, the adjustments made to either the user or the system (or both) to increase usability are aiming for the same result: a simple, intuitive, and efficient experience.

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References:

Issa T. & Isaias P. (2015). Usability and Human Computer Interaction (HCI). Sustainable Design. London: Springer. https://doi-org.ezproxy.library.ubc.ca/10.1007/978-1-4471-6753-2_2

Woolgar, S. (1990). Configuring the user: the case of usability trials. The Sociological Review, 38 (1_suppl), 58-99. https://journals.sagepub.com/doi/10.1111/j.1467-954X.1990.tb03349.x

 

The primary resource selected for this assignment was found through a Google search using the phrase, ‘history of education in Canada.’ The first result in the list was a page on The Canadian Encyclopedia’s website titled History of Education in Canada (Gaffield, 2013).

Using the find functionality (ctrl+F), the term ‘residential’ was found twice on the webpage, identifying two short paragraphs that referred to residential schools and the assimilation of Aboriginal peoples. However, one paragraph did contain a link to another webpage titled Residential Schools in Canada (Miller, 2012)

These resources were found after many attempts to locate and determine appropriate resources for this assignment. Being unfamiliar with educational history or teacher professional development, my aim became to find a resource that summarized the history of education in Canada to see how Indigeneity, Indigenous people, and residential schools were represented in a resource that would be available to the public. The Canadian Encyclopedia was selected on the assumption that encyclopedias are seen as a credible source for information on various subjects and are designed to expand one’s knowledge on topics.

As mentioned above, the find functionality was used to find specific terms within the online text. The results for History of Education in Canada (Gaffield, 2013) are as follows:

• Residential = 2 (in reference to ‘residential schools,’ a search term recommended by the instructor)
• Indian = 0
• Indigenous = 0
• Aboriginal = 9
• First Nations = 0
• Native = 0

The term ‘Aboriginal’ was only presented in the context of education as a mission for colonial assimilation. Also, only one of the nine instances of Aboriginal was capitalized. Based on the information available on the First Nations Studies Program’s (2009) Terminology page, it would have been more respectful to capitalize every instance of the term.

The topic of residential schools’ assimilation of Indigenous people was only referred to in four (of 56) paragraphs. Although there was a link to a separate webpage dedicated to residential schools in Canada if one does not choose to seek this additional information it would be easy to assume that the formal attempts to “undermine the traditional culture” (Gaffield, 2013, para.7) of Indigenous people was extremely minor in the overall context of Canadian education history.

Using the find functionality again, the same list of terms (minus ‘residential)’ was searched within this webpage. The results for Residential Schools in Canada (Miller, 2012) are as follows:

• Indian = 19
• Indigenous = 29
• Aboriginal = 1
• First Nation = 9 (to capture both singular and plural versions)
• Native = 0

While reviewing the above two resources, some of the content prompted me to consider the intergenerational effects of residential schools. This also connected to a third resource that I had found during my initial searches for resources, produced by Stout and Peters (2011) and titled kiskinohamâtôtâpânâsk: Inter-generational Effects on Professional First Nations Women Whose Mothers are Residential. This study examined the ongoing impact of residential school experiences, affecting generations of individuals who did not attend residential schools themselves.

My professional background – both education and experience – includes human resources and workplace learning, so the new questions that came to mind when reading these resources were:

• For those who do not take the time to educate themselves further (i.e., beyond the curriculum taught in Canadian schools), how does this shape their assumptions, either known or unknown as adults? How does that translate into the workplace, hiring practices, management strategies, and tolerance for diversity?
• What other ‘ripple effects’ continue to impact workplaces today as a result of these residential school experiences and how Indigeneity has been – and continues to be – represented in formal educational contexts?

These individuals’ personal circumstances would undoubtedly extend into their professional roles, which lead to questions about how current hiring, training, and other retention strategies systemically discriminate against Indigenous people. While the topic of systemic discrimination is being discussed and examined in many workplaces today in the context of how best to avoid unconscious bias, there is immense value in understanding that some attitudes, habits and contexts of work are connected to influences that run much deeper than the worker’s own personal experiences.

One of the biggest limitations of these results is my own unconscious bias and perspective, as a white-European treaty land inhabitant (Cuthand, 2021) currently living and learning on the Haldimand Tract within the territory of the Neutral, Anishinaabe, and Haudenosaunee peoples.

Another limitation is the digitization of information and assuming that encyclopedias are trusted resources. I grew up going to school in the 1980s and 1990s and was often directed to encyclopedias to further my knowledge on various topics. However, if these resources were produced by other white treaty land inhabitants they may not have had access to the full story of Canada’s educational history.

References

Cuthand, S. (2021, August 30). Introducing yourself as a ‘settler’ creates division. CBC News. https://www.cbc.ca/news/canada/saskatoon/calling-yourself-a-settler-pov-1.6151582

First Nations Studies Program (2009). Terminology. https://indigenousfoundations.arts.ubc.ca/terminology/

Gaffield, C. (2013, July 15; last edited June 18, 2020). History of Education in Canada. The Canadian Encyclopedia. https://www.thecanadianencyclopedia.ca/en/article/history-of-education

Miller, J. R. (2012, October 10; last edited May 20, 2022). Residential Schools in Canada. The Canadian Encyclopedia. https://www.thecanadianencyclopedia.ca/en/article/residential-schools

Stout, R. & Peters, S. (2011). kiskinohamâtôtâpânâsk: Inter-generational Effects on Professional First Nations Women Whose Mothers are Residential. Canada Commons. https://canadacommons.ca/artifacts/2039292/kiskinohamatotapanask/2791735/