Robots in Education

Photo by Alex Knight on Unsplash

We may not see much evidence of robots being used for educational purposes yet, but we can expect to see more. AI technology in the global education market is projected to grow about 43% between 2018 and 2022 (Research and Markets, 2018). Also, it has been predicted that AI will be instrumental in solving the challenge of educating children in regions of the world where there is a shortage of teachers that is “severely limiting human potential all across the globe” (Frey, 2016). The shift from a teacher-centered to a learner-centered approach, along with rapid developments in AI technology, has led to a reconceptualization of “places” of learning. As futurist Thomas Frey (2016) stated, “Education is now on the verge of a major transformation and artificial intelligence-based teacherless education systems are quickly taking center stage.”

While it will be exciting to see the future role that AI will likely play in levelling the field for children worldwide, currently AI-based robots are being used in a variety of ways to support and enhance learning.

• Robots are acting as proxies, helping hospitalized children to connect with their school and continue learning at a distance (Klairmont, 2017; Melendez, 2017; van Hooijdonk, 2017). While parents, teachers, and students are generally satisfied with this use of robots, some students are not happy with the extra attention from classmates, and some teachers are concerned about cameras and microphones monitoring everything that happens in the classroom (Melendez, 2017). 

• Robots are helping students with autism to develop social skills (van Hooijdonk, 2017).

• Since around 2004, robots have played a role in teaching foreign languages to children (Han, 2012). They’ve proven to be effective assistants for language teachers in parts of Asia where it is difficult to find native-speaking teachers of the target language (Han, 2012; Hong, Huang, Hsu, & Shen, 2016; Vogt, de Haas, de Jong, Baxter, & Krahmer, 2017). According to Vogt et al. (2017), however, the technology is still somewhat limited in its ability to recognize children’s speech, so more research and development is needed. In Finland, robots are helping to teach languages and mathematics, too (Reuters, 2018).

• Robots are also playing a role as teaching assistants in higher education. Jill Watson, a robot TA for a university class on artificial intelligence, was so efficient at responding to students’ online questions, that it was some time before they realized that she was a robot (Sprinkle, 2017). 

In every context listed above, robots have proven to be effective motivators for students learning traditional subjects. Furthermore, robots can stimulate students’ interest in programming and robotics (van Hooijdonk, 2017). 

As one might imagine, the use of this type of technology has various social and ethical implications.  In a study by Serholt et al. (2017), teachers who were quick to appreciate the benefits of the technology also expressed a number of doubts regarding its use, including:

• How much responsibility/autonomy should robots be allowed? What kinds of boundaries need to be set to prevent teacher and robot roles from blurring?

• Is it possible for robots to affect younger learners in negative ways, e.g., could children become too emotionally attached to robots or could they assume that the robots are alive? How can teachers, who are knowledgeable about the social and emotional development of children, be included in the design of the technology?

• Who would be held accountable if a problem arose?

Clearly, while there is much excitement as to the different ways in which robots will facilitate learning in the near future, there are some valid concerns as well. What does the future hold for this technology? We may not have to wait much longer to find out.

References

Frey, T. (2016, November 30). Cracking the code for the future of education. Retrieved from https://www.linkedin.com/pulse/cracking-code-future-education-thomas-frey 

Hong, Z. W., Huang, Y. M., Hsu, M., & Shen, W. W. (2016). Authoring Robot-Assisted Instructional Materials for Improving Learning Performance and Motivation in EFL Classrooms. Educational Technology & Society, 19(1), pp. 337–349. Retrieved from https://www.j-ets.net/ETS/journals/19_1/27.pdf 

Klairmont, L. (2017, December 17). Kids isolated by cancer connect online. CNN. Retrieved from

https://www.cnn.com/2017/03/16/health/cnn-hero-leslie-morissette-grahamtastic-connection/index.html 

Melendez, S. (2017). Thanks to telepresence robots, kids can attend school from home. Retrieved from

https://www.fastcompany.com/40419402/thanks-to-telepresence-robots-kids-can-attend-school-from-home 

Research and Markets. (2018, May 9). Global artificial intelligence market in education sector 2018-2022. Retrieved from

https://www.prnewswire.com/news-releases/global-artificial-intelligence-market-in-education-sector-2018-2022-sector-to-grow-at-a-cagr-of-43-36---key-vendors-are-cognii-ibm-microsoft-nuance-communications-pixatel--quantum-simulations-300645568.html

Reuters. (2018, March 27). Techno teachers: Finnish school trials robot teachers. Retrieved from https://www.reuters.com/article/us-finland-school-robots/techno-teachers-finnish-school-trials-robot-educators-idUSKBN1H31XT 

Serholt, S., Barendregt, W., Vasalou, A., Alves-Oliveira, P., Jones, A., Petisca, S., & Paiva, A. (2017). The case of classroom robots: Teachers’ deliberations on the ethical tensions. AI & Society 32(4), pp. 613-631. DOI: 10.1007/s00146-016-0667-2

Sprinkle, T. (2017, November). Robot teachers transform education. Retrieved from https://www.asme.org/engineering-topics/articles/robotics/robot-teachers-transform-education 

van Hooijdonk. R. (2017, February 17). Robots in education are here. And they aren’t going anywhere [Web log post]. Retrieved from

https://www.richardvanhooijdonk.com/en/robots-education-are-here-and-they-arent-going-anywhere/

Vogt P, de Haas M, de Jong C, Baxter P and Krahmer E. (2017). Child-Robot Interactions for Second Language Tutoring to Preschool Children. Frontiers in Human Neuroscience 11. DOI: 10.3389/fnhum.2017.00073

The Impact of AI on Higher Education: Time for a Revolution?

Is it time for higher education to find better ways to meet the needs of today’s learners? Joseph Aoun, President of Northeastern University, clearly thinks so. During an interview with MIT Technology Review (2018), Aoun discussed the impact of AI on higher education and outlined the urgent need for change in institutions of higher learning. Much of what he stated will not be new to most readers, but I recommend viewing the 29-minute video (at the link below) since the brief summary below hardly does the interview justice.  

https://www.technologyreview.com/video/611313/robot-proof-higher-education-in-the-age-of-artificial-intelligence/

Firstly, in terms of how the average, degree-seeking higher education student is educated, Aoun advised a greater emphasis on humanics (defined by Merriam Webster as “the subject or study of human nature or human affairs”), which he described as the interweaving of three literacies: tech literacy (the ability to grasp how machines function and how to interact with them effectively), data literacy (the ability to understand and navigate volumes of data generated by AI), and human literacy (the development of soft skills that cannot be duplicated by machines). Aoun also recommended a combination of real-world (experiential) and classroom education to teach learners to identify personal skill gaps, develop empathy, and better understand the world. 

Secondly, Aoun observed that many lifelong learners have ceased looking to universities for their professional development needs; they are turning to employers instead, and although some organizations are meeting this need, they are also questioning whether it will be worth it in the long run, given that most employees no longer remain with a company for extended periods. Other employers, seeing that their employees’ skills are already obsolete, are taking the initiative to provide training, but they’d prefer that higher education do this so that they can focus on business instead.

One solution, according to Aoun, is for higher education to offer customized, flexible options, consulting with learners to determine their desired outcomes, just as businesses do with their customers, rather than restricting options to degrees and research in a time when learners are already customizing their learning.  As long as institutions continue to restrict admission to their programs based on an established set of criteria, they are turning “customers” away, which no business in its right mind would do. This statement really hit close to home for me—as a lifelong learner who sought information on some courses offered by a local university only to be told that they were strictly for undergraduate students (despite there being a diploma option), I can identify with this. I felt exactly like a customer whose business was being turned away. Like others in this type of situation, I looked elsewhere and found the training I wanted for a reasonable fee at a small, private institution that offered flexible options.

Aoun also suggested that perhaps it’s time for the governments that fuel research and innovation and provide funding for education from Kindergarten to higher education, to consider offering incentives to individuals to encourage lifelong learning in ways that suit them best.

The labour market worldwide is quickly changing: new jobs are being created on an ongoing basis, and it won’t be long before many others become obsolete. A quick Internet search will yield possibly hundreds of results on the topic of job automation, with varying projections on the types and numbers of jobs at risk (Winick, 2018).  Although the news is not all doom and gloom (Lund & Manyika, 2017), Aoun asserted that institutions that fail to place a greater emphasis on lifelong learning are like the railway industry that saw the advent of the airlines but continued with business as usual, assuming that their jobs would not be impacted.

 

Advances in technology have made it necessary for higher education to rethink the options they offer to all types of learners, but according to Aoun, this is not an easy sell. Ironically, though, the same institutions that are hard at work teaching today’s educators to embrace the latest learning theories and adapt their teaching practices to give this generation of learners the skills needed for success in the 21^st century, may find one day that their faculties of education have done their job all too well, as the current generation of students become autonomous learners with well-developed growth mindsets who are capable of customizing their own learning and have little or no need for the traditional options offered by institutions of higher learning.

References

Humanics. (n.d.). In Merriam-Webster’s online dictionary. Retrieved from https://www.merriam-webster.com/dictionary/humanics

Lund, S. & Manyika, J. (2017, November). Five lessons from history on AI, automation, and employment [Web log post]. Retrieved from https://www.mckinsey.com/featured-insights/future-of-organizations-and-work/five-lessons-from-history-on-ai-automation-and-employment

MIT Technology Review (Producer). (2018). Robot-proof: Higher education in the age of artificial intelligence [Video webcast]. MIT Technology Review. Retrieved from https://www.technologyreview.com/video/611313/robot-proof-higher-education-in-the-age-of-artificial-intelligence/

Winick, E. (2018, January 25). Every study we could find on what automation will do to jobs, in one chart. MIT Technology Review. Retrieved from https://www.technologyreview.com/s/610005/every-study-we-could-find-on-what-automation-will-do-to-jobs-in-one-chart/

Recommended Reading

Aoun, J. E. (2018). Robot-proof: Higher education in the age of artificial intelligence. Education Technology Insights, February-March 2018, pp. 11-12. Retrieved from https://www.educationtechnologyinsights.com/magazines/February2018/LMS/