A Robot Teacher for Equality: A Socio-technical Plan


The digital age has transformed people’s lives and how to do business across industries. The advent of Artificial Intelligence and the use of emerging technologies in education promoted new methods of imparting knowledge and teaching methods. The concept investigated the use of robots as teachers, particularly in developing countries and deserted areas, to advance equality to acquire education. Generally, the current adoption in several well-sustainable countries realized its potential, yet it portrayed several limitations and concerns (Newton & Newton, 2019). Additionally, the adoption of similar projects in countries in need of education considered the technical, sociological, economic, and cultural perspectives that witnessed the opposite direction. Mimicking the experience in third world countries could be a different challenge and raise questions about whether to adopt robots or maintain the traditional methods. The presented socio-technical plan considered robot teachers in schools when needed due to the scarcity in obtaining an education.

The Scope

The perception of AI in education took the form of a program or software delivered online or through computers (Ivanov, 2016). However, the field evolved and initiated several disciplines and practices. The use of robotics became widely practiced in several countries, such as Finland (Lynch, 2019). The ‘Robot Teacher’ concept could perform almost entire roles associated with real teachers (Lasso-Rodríguez & Gil-Herrera, 2019). The scope explored the benefits of AI and robotics as part of the academic curriculum and transformation required by the school management, students, and parents simultaneously. However, the demand for education in less fortunate countries and deserted areas encompassed additional challenges in logistics, robot functionalities, specifications, and cultural criteria. In a particular county, each tribe or remote village might have a different language. For example, India has 22 official languages, 121 spoken languages, and more than 19,500 mother tongues (PTI, 2018). 

The Purpose

UNESCO proposed the 2030 Agenda for Sustainable Development aimed to provide equality in education (Houser, 2017). The study examined the benefits that can be delivered through the use of robots and explore the social factors that might play a significant role in the perceived acceptance. The initiative could provide opportunities to millions of students living in poverty. Additionally, the field witnessed a shortage of global teaching that demanded an alternative method to provide a consistent increase of enrolled students (Edwards & Cheok, 2018). Further, the gap in delivering sufficient educational resources was even more severe in the developing countries (Demirjian, 2015). The situation worsened when considering the rural areas in parts of Africa, Asia, and South America, and each encompassed diversity in culture, language, and logistic challenges. Several studies reported that the use of robots provided better teaching results and better engagement from students (Han, 2012; Tanaka et al., 2013). The purpose was to promote equality and the right of free education for all children on the globe with minimized cost and logistic requirements. Additionally, the adoption considered students with special needs that demanded further assistance that might not be available in the developing countries.

Supporting Forces

Several studies stated that children demonstrated better understanding when tutored by a robot than traditional human tutoring (Brown et al., 2013). However, the concluded outcome could not be generalized across entire students, as young children could be more attracted to the robot experience and demonstrated a higher level of attention and attraction (Brown et al., 2013). The advancements in technologies would enhance the flexibility, responses, and adaptability of the robots. The advent of quantum computing could accelerate the interactivity and responses demanded to mimic human perception when dealing with students instantly. The use of solar batteries could enhance the logistic concerns of charging and promote extended usage and maintain longer life in remote areas where electricity could be a privilege. However, the field demanded further investigations to ensure robot continuity in locations that lack or have a scarcity of electricity. The robot connectivity to the Internet through satellite to deliver searching capabilities and navigating the Internet for unexpected raised questions and dialogue communication. Additionally, with Natural Language Processing (NLP) and language translation’s emergence, the language barrier challenge could be resolved and improved significantly.

The ability to deliver education to children with special needs demanded further care and involved humanitarian objectives that could be challenging for several countries. Accordingly, deploying a social robot demonstrated interaction and communication with humans through following particular behaviors (Edwards et al., 2016). A humanoid robot has been used for kids with autism in schools since 2013 (Kim, 2018). A study conducted by So et al. (2019) concluded that social robots demonstrated similar outcomes as human teachers when dealing with children having autism. Such capabilities could be adopted in countries that lack specialized and experienced teachers.

Challenging Forces

The use of robotics in the school could be applied in different situations. Lasso-Rodríguez and Gil-Herrera (2019) stated that the adoption could be through a classical educational robot, while others could be equipped with specific functions to interact with people. De Graaf and Allouch (2013) emphasized that the variables that could impact social robots’ acceptance should cover the utilitarian and hedonic factors. The utilitarian model, such as the Technology Acceptance Model (Davis, 1989), and the derived Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2016) cover the ease of use, and the perceived usefulness hedonic factors encompassed the joy and attraction to the delivered technology. However, the effectiveness of using robots should exceed the regular educational program. The applied methods should use adaptive techniques to monitor students’ engagement and apply behavioral strategies to maintain attention and focus (Brown et al., 2013). Such consideration could raise challenges to robots’ capabilities in instant responses or generating emotional or funny comments. As the study mentioned earlier, younger children demonstrated higher learning effectiveness due to adaptive factors; the adoption should mitigate such expected challenges in other cultures. In that sense, and according to Rose Luckin, a professor at University College in London, emphasized that the robots were not intended to replace human teachers but instead offer a blend of human and AI for the benefits of a better educational program.

Technically, the robot might not deliver the same inspiration as humans, which might be a challenge and a concern. The issues were connected to cultural and social factors that eventually influenced children and students significantly. According to Manyika et al. (2017), the challenges recognized are the incapability of providing emotional and communication skills to students compared to the teachers. There was a necessity to behave appropriately and instantly in education, raising challenges in the instant automated speech recognition. The computational visions remained limited when applied in different environments and domestic settings. Lemaignan et al. (2016) stated that the advancement in sensing technologies to read gestures and postures improved significantly but still faced challenges to robots while accurately interpreting the learner’s social behavior.  Other challenges considered the logistic perspective, as the maintenance might not be available frequently, and demanded new version of robots that have more extended durability, fault-tolerance, and tolerate harsh environment.

Other least concerns were economically sponsoring the project that should involve the United Nations and several global charity organizations due to the funding scarcity in the targeted countries. Socially and politically, several obstacles could involve bureaucratic and corrupt governments that might impact the implementation or even cancel the entire initiative. Such minimal concerns might delay or slow the adoption and discourage many volunteers from participating. Further, other aspects considered the economic factors due to the workforce’s impact and might lead to broad rejection and resistance to the adoption (Lasso-Rodríguez & Gil-Herrera, 2019).


The involvement of robots in education systems involving direct contact with children and students is critical and essential socially and from a humane perspective. The inception might vary significantly across cultures, families, and economic and political factors. Accordingly, the delivered method considers Delphi’s use to gather the different views and opinions better to understand the feasibility and applicability of the project. However, the approach would be extended to include brainstorming and initiating Nominal Group techniques that are considered a step further than brainstorming to add rank and evaluate the processed ideas (Sample, 1984).  Delbecq and Van de Ven (1971) introduced the concept, illustrating the method could be used in different sizes of groups that deliver quick decisions, taking each vote into account. The initiation should include stakeholders from the targeted location to encompass broad, comprehensive issues that were not recognized earlier. The distant locations of particular participants, or in situations such as COVID-19, could be conducted virtually to deliver similar results as physical meetings.

The challenge is that the innovation toward using robotics in teaching covers several elements that demanded diverse expertise and even global and local authority approvals. As the expertise’ opinions are essential to guarantee better results and outcomes (Rowe & Wright, 2001), the exploration should involve experts in different domains such as social, cultural, Information technology, and the involved parties such as teachers, students, and parents. Nevertheless, the initiative demanded cooperation between the United Nations and the authorities; and should involve the concerned people in charge.


Initially, a conceptual view of the plan demonstrated several integrated components that needed to be addressed (see Figure1). The illustration covered the various areas in a flow regardless of the criticality and importance of each part. Leveraging robots and emerging technologies impact societal norms and behavior in people and entities (Winby & Mohrman, 2018), thus playing a significant role in the initiative’s success. In that context, the adoption of robot teachers in developing countries demanded collaboration efforts between the United Nations, an international charity organization, and wealthy nations to provide sufficient funding for the project. A significant consideration for the project’s success relied on the authorities’ cooperation in the designated countries that might threaten the entire initiative. Each country could involve different factors that needed to be resolved before initiating the project. A critical element in several countries was driven by political and bureaucratic aspects that might cause by corruption acts, conservative communities, or cultural and religious traditions that needed to be considered and handled.

Figure 1: Conceptual View of the socio-technical plan

Technically, the available robot teachers comprised diverse functions and shapes and came with different hardware and software components (Benitti, 2012). Serving different cultures demanded customized specifications that needed to be configured. The implementation in deserted areas might face harsh environments that required particular specifications to guarantee more extended durability and service continuity. Further, spare parts and maintenance could be challenging as several areas could be unreachable frequently, demanding higher technical features. There should be an expectation of electricity shortage and internet disconnectivity that required supportive drivers such as the satellite, as mentioned earlier, Internet and solar charging batteries. Eventually, the adoption considered a roadmap and quick-win to evaluate the outcome and the added value. The phase should assess the teaching methods before delivering the results (Yang & Zhang, 2019). The project’s feasibility could encourage implementations in different places globally that lack fundamental rights of learning to children to fight poverty and illiteracy.

Analytical Plan

The evaluation encompassed three different areas that could influence the initiative’s success and drive the entire project to failure. Firstly, and from a technical perspective, the evaluation included the continuity and availability of the robot operations without interruption or frequent maintenance. The issues encompassed several components that impact the performance of the robot. The technical aspects considered the robot functionalities and features that require specific maintenance due to the working environment. The hardware should be designed to work in a harsh climate different from robot teachers available in schools and university premises. The school environment in the targeted places could face challenging issues such as the humidity and temperature that require rigid hardware components. From software perspectives, algorithms demanded continuous updates and maintenance to ensure the robot’s adaptivity and instant response.

Secondly, the evaluation considered the social response to the project and the technology acceptance from different societies with particular cultural behavior toward the technology. Despite the initiatives’ good intentions, the project could be confronted with cultural, traditions, and religious obstacles. Such factors demanded evaluation the society evaluation at the implementation and afterward. In that sense, the assessment covered the students’ disciplines after analyzing whether any added value is recognized. Further, the evaluation should consider the other stakeholders such as the parents, teachers, and the society for the technology acceptance.

Anticipated Results

Every year, in Nepal, almost 1% of the population left the country, seeking education in nearby countries and leading the country to lose youth (Kuo, 2014). The expected result should solve such problems due to its criticality on an entire nation. The desired result could be recognized particularly on the children in the first place. Initially, the initiative provided every student’s rights to receive the proper education and feel equal with other fortunate children in different parts of the globe. Secondly, the relevant success could deliver a broad adoption for higher education students in their villages, rather than migrating to significant cities seeking education. Additionally, the implementations reduced the associated charges that might not be affordable by most students in particular towns and villages. Accordingly, the anticipated results could open doors to thousands of youth to acquire education and enter the workforce. The majority of young people who could not earn an education would end up unemployed with high potentials to turn into illegal activities and join any undesired groups. Strategically, the initiative would effectively reduce unemployment and transform society into a productive and developed place to live and work.


According to Compagni et al. (2015), early experimentation and small implementation of an innovative technology would provide better understanding and the expected influence over society. The process of applying innovations or ideas to become diffused was addressed in the Diffusion of Innovation theory presented by Rogers (2003) and spread across a broad of disciplines. The purpose was to understand how to translate and apply the proposed idea and get pragmatic appeal results. According to Murray (2009), despite the importance of the influences, the researchers should carefully validate the developed innovation. The main objective was to cover the gap of education inequality by providing knowledge and eliminating illiteracy to many children worldwide. The method would provide essential learning and open new horizons to children in developing countries and deserted villages to advanced education methods.

The adoption of the robot teacher could not happen simultaneously through a particular environment or culture. According to the theory, the implementation considered five different categories; even the robot teacher would solve several critical social issues. The lack of academic staff and the crowded classes in several counties deprived students of equal rights in education. However, the process considered an early adoption covering a minor percent of the targeted population to embrace cultural changes. Eventually, the innovation diffusion would consider the deployment gradually to evaluate the outcome and anticipate any unexpected issues. A small project could be applied first to examine the entire stakeholders’ responses and feedback. Based on the output, the initiative could grow and spread to other classes gradually.

The emerging technologies enabled the feasibility and applicability of the initiative. The robot teacher comprised specific software and hardware; however, enabled technologies are critical for its success. Internet connectivity, electricity availability is the main critical success factor. The use of satellite for Internet or the Internet to everybody initiative such as Microsoft’s Airband  (Edmond, 2020) and Facebook drones Aquila project. A similar initiative known as Project Loon transmitted the Internet through solar-powered flying balloons. The robot’s design should maintain durable and tough rigid covers identical to the field notebooks that work under pressure to preserve a challenging environment.

The idea’s ambition considered the quick-wins and the Think Big, Start Small concept to embrace the disruptive technologies, and transform the digital era that unprecedented open potentials in the future. The strategy allowed to portray an ambitious vision with a realistic approach to achieve the desired outcome. The method allowed the adopters to learn from mistakes at affordable costs and offer a learning process for future implementations. The added value impacts thousands of children’s lives and gives them equal opportunities to gain knowledge and obtain equal chances in a new world. The social impact is significantly recognized, impacting the entire generation and impacting living standards in the long run. However; There would be a significant consideration to the diversity of cultures that might result in different perceptions and acceptance from one place to another. In that sense, the socio-technical system could be manifested differently, driven by the other countries’ traditions (Baxter & Sommerville, 2011). Accordingly, every single implementation might deliver another learning lesson that could be beneficial for future use cases. Baxter and Sommerville (2011) stated that adopting the socio-technical plan facilitated the acceptance criteria and the added value to the involved parties. The robot teacher’s primary driver was to deliver value to the children in need of education and promote better education recognition to the targeted community.

Areas of Future Research

The plan has covered a plan to deliver socio-technical initiative to help thousands and millions of students globally. The emerging technologies played a significant role in enabling a robot to perform effectively and efficiently. However, the robot’s adaptivity required a high engagement level with students that demanded higher cognitive abilities. Further research should consider better performance and higher accuracy from algorithms in NLP, especially dealing with children. Additionally, the engagement considered the emotional responses to react to the student’s engagement. The image processing execution required faster computation power and future research areas to investigate quantum computing as an alternative for more rapid responses.


Baxter, G., & Sommerville, I. (2011). Socio-technical systems: From design methods to systems engineering. Interacting with computers23(1), 4-17. https://doi.org/10.1016/j.intcom.2010.07.003

Benitti, F. B. V. (2012). Exploring the educational potential of robotics in schools: A systematic review. Computers & Education58(3), 978-988. https://doi.org/10.1016/j.compedu.2011.10.006

Brown, L., Kerwin, R., & Howard, A. M. (2013, October). Applying behavioral strategies for student engagement using a robotic educational agent. In 2013 IEEE International Conference on Systems, Man, and Cybernetics (pp. 4360-4365). IEEE. https://doi.org/10.1109/SMC.2013.744

Compagni, A., Mele, V., & Ravasi, D. (2015). How early implementations influence later adoptions of innovation: Social positioning and skill reproduction in the diffusion of robotic surgery. Academy of Management Journal58(1), 242-278. https://doi.org/10.5465/amj.2011.1184

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.

De Graaf, M. M., & Allouch, S. B. (2013). Exploring influencing variables for the acceptance of social robots. Robotics and autonomous systems61(12), 1476-1486. https://doi.org/10.1016/j.robot.2013.07.007

Delbecq, A. L., & Van de Ven, A. H. (1971). A group process model for problem identification and program planning. The Journal of Applied Behavioral Science7(4), 466-492. https://doi.org/10.1177/002188637100700404

Demirjian, H. (2015). Teacher Shortage in the Arab World: Policy Implications. Research Paper. Doha, Qatar: Arab Center for Research and Policy Studies.

Edmond, C. (2020, September 1). Airband: The initiative to bring the Internet to everyone, Microsoft. https://news.microsoft.com/on-the-issues/2020/09/01/airband-initiative-rural-broadband-digital-divide/

Edwards, A., Edwards, C., Spence, P. R., Harris, C., & Gambino, A. (2016). Robots in the classroom: Differences in students’ perceptions of credibility and learning between “teacher as robot” and “robot as teacher”. Computers in Human Behavior65, 627-634. https://doi.org/10.1016/j.chb.2016.06.005

Edwards, B. I., & Cheok, A. D. (2018). Why not robot teachers: artificial intelligence for addressing teacher shortage. Applied Artificial Intelligence32(4), 345-360. https://doi.org/10.1080/08839514.2018.1464286

Han, J. (2012). Robot assisted language learning. Language Learning & Technology16(3), 1-9.

Houser, K. (2017, December 13). Why Robots could replace teachers as soon as 2027, World Economic Forum. https://www.weforum.org/agenda/2017/12/why-robots-could-replace-teachers-as-soon-as-2027

Ivanov, S. H. (2016, June). Will robots substitute teachers? In 12th International Conference “Modern science, business, and education (pp. 27-29).

Kim, M. (2018, February 9). The Social Robot Teacher, BOLD. https://bold.expert/the-social-robot-teacher/

Kuo, L. (2014, January 25). Nepal’s poor education system is creating greying ghost towns at the “roof of the world.” Quartz India. https://qz.com/india/225855/nepals-poor-education-system-is-creating-greying-ghost-towns-at-the-roof-of-the-world/

Lasso-Rodríguez, G., & Gil-Herrera, R. (2019). Robotic Process Automation Applied to Education: A New Kind of Robot Teacher? In ICERI2019: 12th annual International Conference of Education, Research and Innovation.

Lemaignan, S., Garcia, F., Jacq, A., & Dillenbourg, P. (2016, March). From real-time attention assessment to “with-me-ness” in human-robot interaction. In 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (pp. 157-164). IEEE. https://doi.org/10.1109/HRI.2016.7451747

Lynch, M. (2019, April 16). The Rise of The Robot Teacher, The Tech Edvocate. https://www.thetechedvocate.org/the-rise-of-the-robot-teacher/

Manyika, J., Chui, M., & Miremadi, M. (2017). A future that works: AI, automation, employment, and productivity. McKinsey Global Institute Research, Tech. Rep60.

Murray, C. E. (2009). Diffusion of innovation theory: A bridge for the research‐practice gap in counseling. Journal of Counseling & Development87(1), 108-116. https://doi.org/10.1002/j.1556-6678.2009.tb00556.x

Newton, D. P., & Newton, L. D. (2019). Humanoid Robots ads Teachers and a Proposed Code of Practice, Frontiers in Education. https://www.frontiersin.org/articles/10.3389/feduc.2019.00125/full

PTI. (2018, July 1). More than 19,500 mother tongues spoken in India: Census, The Indian Express. https://indianexpress.com/article/india/more-than-19500-mother-tongues-spoken-in-india-census-5241056/

Rogers, E. M. (2003). Diffusion of innovations/everett m. rogers. NY: Simon and Schuster576.

Rowe, G., & Wright, G. (2001). Expert opinions in forecasting: the role of the Delphi technique. In Principles of forecasting (pp. 125-144). Springer, Boston, MA. https://doi.org/10.1007/978-0-306-47630-3_7

Sample, J. A. (1984). Nominal group technique: An alternative to brainstorming. Journal of Extension22(2), 1-2.

So, W. C., Wong, M. K. Y., Lam, W. Y., Cheng, C. H., Ku, S. Y., Lam, K. Y., Huang, Y., & Wong, W. L. (2019). Who is a better teacher for children with autism? Comparison of learning outcomes between robot-based and human-based interventions in gestural production and recognition. Research in developmental disabilities86, 62-75. https://doi.org/10.1016/j.ridd.2019.01.002

Tanaka, F., Takahashi, T., Matsuzoe, S., Tazawa, N., & Morita, M. (2013, November). Child-operated telepresence robot: A field trial connecting classrooms between Australia and Japan. In 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 5896-5901). IEEE. https://doi.org/10.1109/IROS.2013.6697211

Venkatesh, V., Thong, J. Y., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the association for Information Systems17(5), 328-376.

Winby, S., & Mohrman, S. A. (2018). Digital socio-technical system design. The Journal of Applied Behavioral Science54(4), 399-423. https://doi.org/10.1177/0021886318781581

Yang, J., & Zhang, B. (2019). Artificial intelligence in intelligent tutoring Robots: A systematic review and design guidelines. Applied Sciences9(10), 2078. https://doi.org/10.3390/app9102078

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s