AI in Open and Distance Education
Introduction
[編輯]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.
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.
Advantages and Disadvantages
[編輯]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.
- Permanent: as long as the system and program are not changed, artificial intelligence will not change.
- Easier to reproduce and spread: easier to move data from one computer to another when compared to sharing knowledge from one human to another.
- Consistent: artificial intelligence is a consistent computer technology, whereas natural intelligence has a tendency to change.
- Can be documented: each activity carried out by artificial intelligence can be easily tracked while natural intelligence is difficult to reproduce
- Able to do work faster and better.
- 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
- Features that were liked in students』 answers were determined as:
- 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
- Students stated the positive sides of the system as follows:
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
Advantage | 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
Disadvantage | Sources |
time-consuming (deep learning) | Karal et al. 2014, Teng 2019 |
fixity | 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
[編輯]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.
Bibliography
[編輯]Chakrabarti, C., Luger, G.F.: Artifcial conversations for customer service chatter bots: architecture, algorithms, and evaluation metrics. Expert Syst. Appl. 42(20), 6878–6897 (2015). https://doi. org/10.1016/j.eswa.2015.04.067
Drigas, A., & Dourou, A. (2013). A review on ICTs, E-learning and artificial intelligence for Dyslexic’s assistance. International Journal of Emerging Technologies in Learning (iJET), 8(4), 63. doi:10.3991/ijet.v8i4.2980
Fadzil, M., & Munira, T. A. (2008, August). Applications of Artificial Intelligence in an Open and Distance Learning institution. In 2008 International Symposium on Information Technology (Vol. 1, pp. 1-7). IEEE.
Fang, L., & Zhang, J. (2019). Thoughts on the application of artificial intelligence in exceptional child education. Journal of Physics: Conference Series, 1325, 12104. doi:10.1088/1742-6596/1325/1/012104
Fernoagă, V., Stelea, G., Gavrilă, C., & Sandu, F. (2018). Intelligent education assistant powered by chatbots. The International Scientific Conference eLearning and Software for Education, 2, 376-383. doi:10.12753/2066-026X-18-122
Goda, Y., Yamada, M., Matsukawa, H., Hata, K., & Yasunami, S. (2014). Conversation with a chatbot before an online EFL group discussion and the effects on critical thinking. The Journal of Information and Systems in Education, 13(1), 1-7. doi:10.12937/ejsise.13.1
Goel, A. K., & Joyner, D. A. (2017). Using AI to teach AI: Lessons from an online AI class. AI Magazine, 38(2), 48. doi:10.1609/aimag.v38i2.2732
Goksel Canbek, N., & Mutlu, M. E. (2016). On the track of artificial intelligence: Learning with intelligent personal assistants. International Journal of Human Sciences, 13(1), 592. doi:10.14687/ijhs.v13i1.3549
Hedayati, M., Kamali, S. H., & Shakerian, R. (2012). Comparison and evaluation of intelligence methods for distance education platform. International Journal of Modern Education and Computer Science, 4(4), 21-27. doi:10.5815/ijmecs.2012.04.03
Jin, L. (2019). Investigation on potential application of artificial intelligence in preschool Children’s education. Journal of Physics: Conference Series, 1288, 12072. doi:10.1088/1742-6596/1288/1/012072
Karal, H., Nabiyev, V., Erümit, A. K., Arslan, S., & Çebi, A. (2014). Students』 opinions on artificial intelligence based distance education system (artimat). Procedia - Social and Behavioral Sciences, 136, 549-553. doi:10.1016/j.sbspro.2014.05.374
Kose, U. (Ed.). (2014). Artificial Intelligence Applications in Distance Education. IGI Global.
Kusumadewi, Sri. (2003). Artificial Intelligence (Teknik dan Aplikasinya). Graha Ilmu.
Liang, X., Yang, X., Yin, S., Malay, S., Chung, K. C., Ma, J., & Wang, K. (2020). Artificial intelligence in plastic surgery: Applications and challenges. Aesthetic Plastic Surgery, doi:10.1007/s00266-019-01592-2
Liu, Q., Huang, J., Wu, L., Zhu, K., & Ba, S. (2019). CBET: Design and evaluation of a domain-specific chatbot for mobile learning. Universal Access in the Information Society, doi:10.1007/s10209-019-00666-x
Pereira, J., Fernández-Raga, M., Osuna-Acedo, S., Roura-Redondo, M., Almazán-López, O., & Buldón-Olalla, A. (2019). Promoting Learners』 Voice Productions Using Chatbots as a Tool for Improving the Learning Process in a MOOC. Technology, Knowledge and Learning, 24(4), 545-565.
Putra, D., & Triastuti, E. (2019). Application of E-learning and artificial intelligence in education systems in indonesia. International Journal of Computer Applications, 177(27), 16-22. doi:10.5120/ijca2019919739
Teng, X. (2019). Discussion about artificial Intelligence’s advantages and disadvantages compete with natural intelligence. Journal of Physics: Conference Series, 1187(3), 32083. doi:10.1088/1742-6596/1187/3/032083
Shorey, S., Ang, E., Yap, J., Ng, E. D., Lau, S. T., & Chui, C. K. (2019). A virtual counseling application using artificial intelligence for communication skills training in nursing education: Development study. Journal of Medical Internet Research, 21(10), e14658-e14658. doi:10.2196/14658
Sterne, J. (2017). Artificial intelligence for marketing: Practical applications. Newark: John Wiley & Sons, Incorporated.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1-27. doi:10.1186/s41239-019-0171-0