Artificial Intelligence in Mobile Learning
What is Artificial Intelligence, Machine Learning and Deep Learning?
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Artificial Intelligence in computer science is the ability of computing machines to imitate and simulate human-like intelligence and emotions. Instead of computer programmers writing the programs to make computers perform a task, artificial intelligence machines take large amounts of data set, which they interpret, understand and apply their learnings to make decisions and perform the tasks on their own. The term artificial intelligence can better be explained by taking an example of Facebook which identifies the faces in the timeline photographs. It takes the approach of supervised machine learning and identifies the people in the new images by learning from the already labelled images by millions of Facebook users. AI is further divided into machine learning and deep learning. Machine learning is when the programmer labels the data-set to help machines understand, learn and predict the outcome of the new data-set. Deep learning is when the machine recognizes the patterns among data, clusters the data and learns by itself to predict the outcome of the new data when a big, unorganized and random data-set is provided to it
How is it used?
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"Artificial Intelligence" by Bovee and Thill
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Experts systems take the knowledge from it’s knowledge base and help the user to solve the problem. The experts in the field enter the data in the knowledge base and the systems use that knowledge to interpret and solve the complex problems for the non-expert users.
"Google Translate" by jonrussell
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With natural language processing computers are able to interpret the words in the speech with respect to the context. The sentiment analysis of NLP is able to extract emotions, ambiguity and confusion from the text.
"Driverless Cars" by mikemacmarketing
Neural networks similar in structure and function like human neural networks, have three layers which take the input, do the computations in hidden layers and give the result using output layers. Neural networks along with machine learning help the smart phones to keep the face in focus while clicking the picture. With it's intelligent system it also helps in driving cars using camera, sensors and without human intervention
"Beagle using Siri" by technodad
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The speech recognition AI machines take the input in the form of speech and give the desired search result in the form of text or voice. It can also recognize the voice and identifies the person. It is used in smart speakers, smart homes, digital assistants and mobile device applications.
"#Health check-in’s are surprisingly fun with #lark #chatbot app. Who knew an #AI conversational bot be like a friend?" by Mark Koester
Virtual agents also called chatbots with their intelligent communication system works as online customer service representatives and tutors.
"Thinking Machine 4" by viegas
In reinforcement learning , the machines are made to do repetitive tasks and are rewarded when the correct actions are performed by machine.Over a course of time the machine learns to perform those tasks that will increase its rewards.
AI in Education and Mobile Learning
Artificial Intelligence in education system adopt various facets ranging from interactive, personalized learning to virtual reality. With it's adaptive approach AI uses data mining and learning analytics to understand the pedagogical as well as the learner model, predicting the most relevant and personalized learning experience appropriate for a student. In education systems AI with it's voice, face recognition, AR/VR and sensing technologies provide an efficient grading system and accelerate the growth of smart schools. It works with instructor ( as cobots) in a collaborative way to help with the instruction and the assessment. Intelligent tutoring systems like MATHia, Why2Atlas and Viper have been used by educators to improve different pedagogical tools, helping in assessment and tracking the progress of the students. Along with VR, AI is used to train the medical students and prepare them for the real-world experiences. Adaptive and intelligent Web-based education systems instead of using"just-putting-it-on-the-web" approach understands the learners' knowledge, skills, preferences as well as performance capabilities and adapts itself to needs of the learner.
AI also helps in performing the administrative tasks for teachers as well as for the management. TurnItIn and Ecree are the intelligent based systems that help in grading, checking for the plagiarism on students' work and helping the instructor with the administrative tasks. Applications like Grammarly and PaperRater help the instructors in grading and providing the feedback to the students. AI with its' animated characters in the form of chatbots help students in providing effective teaching and answering students' queries in the form of conversation and dialogue. By providing the customized and personalized curriculum Knewton provides the real-time recommendations to students for enhancing their learning. Immersive reader, CALL and Cerego improves the learning and provides the enriching experience to the students.
With the better processing power and 5G networks, mobile learning is becoming convenient and accessible for learners as well as instructors. Also, with innovative technologies, Educational Big Data, learning analytics and smart learning cloud services the use of artificial intelligence as immersive technology in the learning environment is becoming the new norm.
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The Substitution, Augumentation, Modification and Redefinition model (SAMR) shows how the technology in particular the application softwares will impact different layers of the model. The Artificial Inteligence in Education (AIED) will be present in all layers with its' impact growing as we move down the stack.
Apps used in education
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Quizlet
This app help in user generated flash cards. It also supports collaborative editing and supports images/audios in flash cards. It provides personalized and NLP features.
Cognii
This app is virtual assistant which adapts students in a learning style which involves chatbot.
Century
Personalized learning with AI integrated technology. The app supports teachers as well as students in online home learning
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Knewton
It provides an adaptive learning environment with personalized learning for higher education
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Cerego
This app will help learner to keep track of the progress with smart notifications, highlighting the learners' strengths and suggessting the areas of improvement.
Duolingo
Duolingo with its' game based learning environment assesses the learner and delivers the personalized learning.
Querium
This virtual tutor diagnoses where the learner is finding difficulty and provides customized solutions to the problems.
Ecree
It is an on-demand writing tutor which gives real-time feedback to users on their writing skills.
Prospect of AI in education
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Challenges to AI in education
With advancement in AI technology and the growing use of AI in the education system, there are concerns and challenges which the government as well as private corporations need to address so that the full potential of AI is unleashed in a constructive way. The speed at which the research and innovation is going on for AI, the public and state policies are not yet prepared for the change. The public policies should come up with solutions and answers when it comes to regulations and data ethics. Public and private partnership is required in the developing countries to strengthen the AI training and research in universities and public sectors. Due to lack of electricity, internet, digital literacy and data costs, the underprivileged population is likely to be excluded from AI driven education systems which will increase the digital divide between developed and under-developed countries. Educators as well as administrators need to be trained and prepared for AI-powered education. There is a large gap between understanding of the potential of AI in education and the actual implementation of AI in the learning processes by the educators. So the teachers need to be prepared for the use of AI in different forms in their pedagogical and learning processes. The AI system in education is driven by data. If in case the real-time data is not collected properly or there is discrepancy in data, the algorithms of AI will not be able to predict and provide the accurate forecast. Therefore, the quality and reliability of the data is a major concern when it comes to efficient working of artificial intelligent systems.
Also, the research in AIED should meet the requirements and needs of the teachers. The schools as well as education institutions might not be prepared to integrate this technology in their pedagogical and learning processes due to lack of technological infrastructure.
Data privacy, security and ethics also come into consideration when AI approaches are used in the education system. Large concentration of data in web results in security concerns and the big companies having access to individual's personal data could use the data for their own interest.
Also, the big question is, what if in case the predictive algorithms end up giving wrong results and making incorrect decisions for students? Who will be responsible and liable in such circumstances?
References:
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2. Get started with artificial intelligence – IBM Developer
3. Wayne, H, Bialik, M, Fadel, C. (2019).Artificial Intelligence In Education Promises and Implications for Teaching and Learning.The Center for Curriculum Redesign.
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4. Artificial intelligence in education: challenges and opportunities for sustainable development - UNESCO Digital Library
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7. AI in Education Market Size, Share, Trends, Analysis, Growth, Forecast (verifiedmarketresearch.com)
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