AI in Open and Distance Education

出典: フリー教科書『ウィキブックス(Wikibooks)』


In today’s world, we can hear the word “AI” many times a day through different kinds of media. The term “AI” refers to Artificial Intelligence, which generally can be considered as a technology that can think or solve problems just like a human does. And “AI” can achieve this progress by studying the information they gained from the surroundings. Nowadays, AI has been used in many fields to create convenience for human lives. Such as healthcare, economics, art, video games, etc. And there is no doubt that the field of education is also a field in which AI has been applied. In the previous studies, AI applications in education can be found in different subjects, such as nursing education (Shorey et al., 2019), medical science(Liang et al. 2020), marketing (Sterne, 2017), etc. And the research can also be divided by level of education such as child education (Fang & Zhang, 2019; Jin, 2019), and the higher education (Zawacki-Richter et al., 2019). Furthermore, recently, AI is also becoming a vogue in e-learning and mobile learning (Goda et al., 2014; Liu et al., 2019). As Kose (2014) mentioned, “ the e-learning technique and more generally distance education approach are highly associated with the applications of Artificial Intelligence.” Likewise, the field of Open and Distance Education is also considered to be a field which relies heavily on human- machine interactions (Fadzil & Munira, 2008). Such as Open Universities and MOOC. As AI is becoming a bigger part of our life, the interaction between humans and machines can be imagined to be more important. Thus, it is necessary to review the application of AI in the Open and Distance Education field to explore how it helped or will help to assist teaching and learning.

Therefore, we organized this chapter as follows: First, we found out some cases about the application of AI in Open and Distance Education. Second, we discussed the merits and demerits of the use of AI in the field of Open and Distance Education. And finally, we proposed some possible further research topics as a conclusion of this chapter based on the findings.

Examples of AI use in Open and Distance Education[編集]

The application of AI in Open and Distance Education can be considered as a support for both teachers and students to enhance the effectiveness and efficiencies of teaching and learning (Kose,2014). And the support can from different ways, for example, to apply AI in the educational tools, materials, or assessment, etc. In this part, we reviewed some papers of Open and Distance Education and chose some cases of AI application.


Karal et al. (2019) assessed an artificial intelligence-based distance education system called ARTIMAT, which was designed to develop mathematical problem-solving skills, in terms of the conceptual competence, the ease of use and students’ contribution to the problem-solving process (Karal et al., 2019). The ARTIMAT was experienced by 59 students in 10th grade in an Anatolian High School in Trabzon. In the following section (3. Advantages and Disadvantages), more features of the AI system will be discussed. However, to explain briefly, the AI system was found to be very effective and satisfying according to the student interviews.


There are also some contexts where AI is used especially for students with special needs (e.g., dyslexia). As Drigas & Dourou (2013) argue, children with dyslexia have special learning skills, and thus most of the time only specialized institutions know better and are able to support their reading difficulties. Then, a software called the AGENT-DYSL was developed by researchers. According to Drigas & Dourou (2013),

the main features of the AI system are: propose a reading system for dyslexic children with personalized attention, through presentation of customized reading materials integrates into school environment takes into account the context of learning Also, the unique features of the AI software program are: personalized assistance combines speech recognition state recognition via image profiles error via adaptive and personalized support

Thus, it appears that AGENT-DYSL is able to support such particular students in many aspects. We believe this can be applied to more broad contexts where not only students with special needs but also any students are learning. For example, in Japanese public schools, there are usually some students with special needs in classes. Moreover, there are also some students who do not need specific support, but still face some difficulty in learning. Therefore, integration of such AI systems into the school environment would provide students with personalized assistance with taking into account the context of their school environments.

Repeated Reading Adaptive Fluency Tutor (R2 aft)[編集]

Similar to the previous AI system, there seems to be a lot of AI systems which particularly focus on reading assistance. The R2 aft tutor (Repeated Reading Adaptive Fluency Tutor) was developed to improve reading fluency among students with dyslexia. Since this AI system is still in the process of evaluation, it is not very used worldwide yet. Therefore, not much information was provided on the Internet. However, according to Drigas & Dourou (2013), an important part of the R2 aft tutor is that it generates a text to be read through a story assembly engine called TASA (Text And Story Assembler).

Spatial Math Tutor[編集]

There is also a cognitive tool for better performance on mathematical tasks. The AI system is called Spatial Math Tutor which was developed, tested, and incorporated into an online tutoring environment (Drigas & Dourou, 2013). Through graphical representation and the manipulation of CG objects, the AI system is considered a beneficial tool for learners taking into account all the assistive 3D graphic technology and interaction tutoring (Drigas & Dourou, 2013).

Chatbot for peer-assessment[編集]

A chatbot , as an Artificial Intelligence technology, is known as a conversational agent, which refers to a computer program engaging in conversation or simulating informal chat communication between a human and a computer program in natural language (Chak & LugChatter, 2015). And as it was mentioned by Liu et al., (2019), “In the field of education, the role of chatbots has been highlighted in the context of e-learning and has received considerable attention.” In Pereira et al., (2019) ’s research, mobile based chatbots were used to record the voices of the MOOC students, so they can do the peer- assessment with more motivation and participation. According to the research of Pereira et al., (2019), we can imagine that since today’s students tend to rely on their personal device like mobile phone, or social media application, scholars too are beginning to insert AI to Open and Distance Education through a mobile phone assisted learning system. Thus, when talking about AI applications, we should not only think about a computer, but devices like mobile phones should also be considered.

Using AI tutoring agent to teach[編集]

In Goel & Joyner (2017) ’s study, they set a foundation online AI course for an online program of an institution to solve the problem of the rapidly growing need for AI courses. And the courses are delivered by the MOOC provider Udacity. In the research, AI was used in two ways: One is intelligent tutoring of AI concept; and another is Authentic engagement in AI research. For the former, exercise were set in the video lesson, “nanotutors” are set to support the exercises. As Goel & Joyner (2017) mentioned, the role of the “nanotutors” is to “ guide students’ understanding of one narrowly defined skill such as completing a semantic network for a particular problem or simulating an agent’s planning in the blocks world”. According to the students satisfaction survey, they found that most of the students agree about the function of the “ nanotutors ” in helping them to understand the material. As for the latter, the AI course can allow students to re-create the AI agents as an authentic engagement. And it helped the students to know the dynamic and emerging theories of AI. Although, this study seems to be a specific one, since it use AI to teach AI. However, we can also gain some enlightenment from the practice that AI may us to teaching itself. Moreover, what we found interesting in this paper is that, it mentioned that the video lesson itself may not be interactive as a general course in a school situation, the discussion part like a forum may play an important role on that part. Therefore, inserting AI to facilitate interaction seems to be an interesting topic in the future study.

Application of AI in distance education in Indonesia[編集]

According to Putra & Triastuti (2019), when assessing whether a country has a more positive image on integration of AI into distance educational contexts, “readiness” will be a useful criteria. Specifically, they argue that readiness for the application of AI in distance education must consider the specific influence on each situation, institution or learning program (Putra & Triastuti, 2019). They strongly argue that although various factors have an influence on implementation and effectiveness of AI, “readiness” will be a critical success factor. From this perspective, Putra & Triastuti (2019) analyzed the implementation of AI in distance education in Indonesia. Then, they state that the following points are some issues Indonesia has to deal with at this time. Indonesia needs technical training for teachers.

  • Indonesian teachers need to understand their role as facilitators, collaborators, mentors, trainers and study partners for students in the e-learning process.
  • Indonesian government needs to improve facilities and infrastructure that support distance education in order to facilitate the needs of the latest AI technology, such as:
    • Reach of electricity to the region
    • Fast internet connection
    • Computers with the latest systems

Advantages and Disadvantages[編集]

There are both advantages and disadvantages to AI. In this section, the advantages and the disadvantages of AI will be discussed in comparison with those of natural intelligence (NI). In particular, 10 advantages and 2 disadvantages of AI will be discussed.

First of all, according to Putra & Triastuti (as cited in Kusumadewi 2003), AI has many advantages when compared to intelligence possessed by humans (=natural intelligence/NI). Specifically, they explain six advantages of AI.

  1. Permanent: as long as the system and program are not changed, artificial intelligence will not change.
  2. Easier to reproduce and spread: easier to move data from one computer to another when compared to sharing knowledge from one human to another.
  3. Consistent: artificial intelligence is a consistent computer technology, whereas natural intelligence has a tendency to change.
  4. Can be documented: each activity carried out by artificial intelligence can be easily tracked while natural intelligence is difficult to reproduce
  5. Able to do work faster and better.
  6. The cost is cheaper than bringing in an expert.

This suggests that permanency, shareability, consistency, recordability, efficiency, and cheapness are six major advantages of using AI.

As for consistency and efficiency out of the six major advantages of using AI, Teng (2019) also argues that AI would outcompete human beings by its accuracy and efficiency when the task is highly repetitive and is not very complex.

Moreover, from a different perspective, Karal et al. (2014) conducted an interesting research regarding students’ opinions on artificial intelligence based distance education system. The purpose of the research was to evaluate an AI system called ARTIMAT, which was developed to increase students' problem solving skills. In order to evaluate the AI system, 59 students in 10th grade in an Anatolian High School in Trabzon participated in the research. Anatolian High Schools are public high schools in Turkey that admit their students according to high nationwide standardized test (TEOG) scores. The students were divided into two groups, and the two groups experienced the AI for two hours for three weeks (six weeks in total). All the students experienced the AI system either in a computer lab or in a way that each student used their computer alone. Also in order to obtain further opinions and thoughts from the students regarding the AI system they experienced, written interview forms were used.

In the data collection, the students' opinions and thoughts about the AI system were compiled regardless of the students' grade or gender. Although there were a total of seven questions asked to the students who participated in the interview, two questions will be retrieved in this current section. The two questions and the answers from the students are as follows.

Question 1: Which one of the features of the system did you like the most/least?

  • Features that were liked in students’ answers were determined as:
    • Providing individual learning
    • Being a more instructive system which is easier to remember
    • Providing the identification of the problem
    • Solving systematically the question step-by-step with different methods (individuality)
    • Trying different solutions courtesy of the system
    • Being easy to use
    • Visual design
    • Feature that students can add photos by creating their own profiles (individuality, visuality)
    • Students being able to communicate with each other via the system
  • Features that were not liked in students’ answers were determined as:
    • Being unable to move directly to the result
    • The obligation to follow the steps
    • Losing time as there is a different solution

Question 2: Was the system helpful for your problem solving process? Can you explain?

  • Students stated the positive sides of the system as follows:
    • It shows what should be done in the process of problem solving
    • It helps students think about the solution of the problem
    • It increases the knowledge about the solution of the problems It strengthens the feature of judgment
    • It contributes to the understanding of the problem
    • It makes it easier to solve the problem when the user is familiar with using the system
    • It warns when the wrong solution is selected It develops the habit of systematic problem solving

As can be seen from the students' answers to the interview questions, it appears that there are not only advantages but also some disadvantages from the learners' (actual users') point of view. In particular, individuality, easiness, visuality, and communicativity seem to be four major advantages which were elicited from the interviews. On the other hand, Fixity of learning process and time-consuming seem to be two major disadvantages if using AI which were elicited from the interviews.

Considering the disadvantage of time-consuming, Teng (2019) also argues it as the disadvantage of using AI in comparison with natural intelligence (NI). Teng (2019) even provides an example to understand how AI is sometimes time-consuming compared to NI. Teng (2019) explains that although most people can recognize a movie star, even if they have only had a glance at his or her new movie on TV, thousands of pictures from different perspectives of that star are needed if you want to train an AI to recognize him or her. Teng (2019) also describes that this function of the human brain is known as one-shot learning, whereas the function of AI is known as deep learning. Teng (2019) concludes that it appears that our brains work in a more flexible way which has something to do with the origin of natural intelligence.

As this paper has discussed so far, it seems that there are both advantages and disadvantages of using AI in the context of distance education. The following two tables (Table 1 and Table 2) shows the integration of all ideas of advantages and disadvantages which were argued by different researchers.

Table 1 Advantages of Using AI in Distance Education
Adcantages Sources
permanency Kusumadewi 2003
shareability Kusumadewi 2003
consistency (accuracy) Kusumadewi 2003, Teng 2019
recordability Kusumadewi 2003
efficiency Kusumadewi 2003, Teng 2019
cheapness Kusumadewi 2003
individuality Karal et al. 2014
easiness Karal et al. 2014
visuality Karal et al. 2014
communicativity Karal et al. 2014

Table 2 Disadvantages of Using AI in Distance Education
Disadvantages Sources
time-consuming (deep learning) Karal et al. 2014, Teng 2019
fixity of learning process Karal et al. 2014

As the two tables show, it is not an exaggeration to say that there are many advantages of using AI in distance education. However, it is important to recognize that there are also some disadvantages of using AI in distance education. What we think is the most important thing is that educational institutions and developers should consider the disadvantages of using AI, and make improvements or plan additional support to solve those disadvantages.

For example, as for the disadvantage, time consuming, creating a big platform which any developers or educational institution can access and obtain useful data to create an AI system which suits their context would be a possible solution. In other words, if it takes time to make the AI system learn the pattern, accumulating many cases and using the big data would support the AI system learn many patterns before being integrated to educational institutions.

As for the disadvantage, fixity, it was actually interesting that some students answered during the interview which was conducted by Karal et al. (2014) that

  • Being unable to move directly to the result
  • The obligation to follow the steps

are some features that the students did not like about the AI system they experienced. These comments imply that

  • students are not able to move directly to the result
  • students are guided to follow certain steps in the process of learning.

Therefore, what these students’ answers mean is that the AI system provides students with not only results but also knowledge of how to solve questions. Moreover, the students’ answers also suggest that the AI system provides students with well-organized small-steps for them to learn step by step, and to prevent students from getting off track. What these students’ comments about disadvantages infer is that some positive features might be mistaken by students in contrast to the original intention of developers.

Further Research and Topics[編集]

According to the research and analysis above, we can have an overview about the recent findings of the application in Open and Distance Education. First, in the light of the cases we found, we could know that in the field of Open and Distance Education, an insertion of AI in the tutor system seems to be a vogue. Moreover, the AI tutor systems are designed not only for the better performance of the students, but may also be for an efficient assessment progress. And we can also learn that for some step- oriented subject, like math, and AI itself, AI tutor system may also play a role as a guide to support the understanding of the certain skills. On the other hand, we could imagine that scholars also pay attention to the assistant for students with special needs. Furthermore, we could know that in addition to how to design, the researchers also focus on how to design effectively. The so called “readiness” are mentioned, which we considered to be the environment of a certain region or background.

As for the further research, according to the previous studies about both the AI application and the pros and cons of using AI, we suppose that there may be some future topic or trend about the following field. First, in view of the disadvantages of the use of AI mentioned above, a more effective model of AI application design may be a potential topic. Moreover, as the application progress goes on, more research from a students’ perspectives is needed. Secondly, inserting AI in the interaction part also seems important, which is also mentioned in the previous study above as the key word “communicate”. Lastly, we also gain some idea from the research of Fadzil & Munira (2008), who tried to explore some field whereby AI may be potentially used in an open and distance learning institution by using the case of Open University Malaysia (OUM), except the field of tutor for assessment, they also mentioned some ideas, such as: to help the students choose the most suitable course, to scheduling the classes they chose, to help with the plagiarism detection, and to help to retain learners and adapt to their diverse needs and backgrounds. It seems that in this paper, the security of the university, learner diversity, and infrastructure construction may also be a potential topic of the application of AI.


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