Learning styles are a common teaching tool within the education industry. Learning styles are the idea that every student has a specific method of learning that will produce the best outcome. One of the most popular learning style methods is VAK. VAK stands for visual, auditory, and kinesthetic. According to this theory, some students learn best by seeing the material (visual), others learn best by hearing the material (auditory), and still others learn best with a hands-on approach. The VAK is only one example of a learning style model. Multiple other models exist, some of which contain over 170 different learning styles.
While learning styles are prevalent in the education industry, they are contested. However, it is inarguable that tailoring education toward each student improves learning outcomes. With an average class size of twenty students, teachers simply don’t have the time or resources to create individualized lessons for each student. However, emerging technology in artificial intelligence is proving a helping tool to bridge the gap between individualized learning and teacher’s time constraints. Some of these tools include chatbots, interactive experiences, and predictive analytics.
Teaching with Chatbots
Chatbots utilize artificial intelligence and natural language processing to offer immediate and individualized assistance to students. When students have questions, they can consult the chatbot to quickly receive assistance, even if their teacher is busy. This real-time support ensures students can get the help they need precisely when they need it, minimizing confusion.
Chatbots can also adapt their teaching style and content delivery depending on the student’s learning pace and preferences. If a student has trouble understanding a teacher’s explanation of a topic, chatbots can help fill this gap. Chatbots can also create personalized quizzes, practice exams, and recommend additional material to gauge students’ comprehension and fill in any knowledge gaps.
One example of utilizing chatbots in education is at the University of Mercia in Spain. This university implemented a chatbot to answer common questions students have about the campus and courses. Of the almost 40,000 questions the chatbot received, it was able to correctly answer 91%. In addition to providing students with the answers they needed, this chatbot had the added benefit of increasing student motivation and saving administrators’ time.
Interactive experiences
Interactive experiences adjust learning content and exercises based on student performance. For example, if a student demonstrates a basic understanding of a concept, interactive experiences can provide more advanced material to further the student’s learning. Interactive experiences also work in the reverse. If a student is struggling with a particular concept, an interactive experience can provide more rudimentary material until a student more fully understands the concept and is ready to progress.
Two of the most popular interactive experience platforms are Khan Academy and Duolingo. Khan Academy uses AI algorithms to analyze data from the millions of students using the platform. Based on this wealth of data, Khan Academy can adjust learning materials and exercises to ensure students are challenged and engaged without overwhelming them. Using this technology, Khan Academy has grown student engagement, improved academic outcomes, and optimized learning experiences.
While Khan Academy teaches students a variety of different topics, Duolingo focuses on language learning. Like Khan Academy, Duolingo utilizes data from its users to analyze strengths and weaknesses and tailor content to help students improve their language skills. Duolingo also utilizes AI algorithms to analyze the pronunciation and speech patterns of students. Based on this data, Duolingo can provide additional instructions to help students not just understand the language but speak it like a local.
Predictive Analytics
Unfortunately, many students do not reach their academic goals and instead drop out of school. While there are numerous academic and socio-economic reasons for dropouts, one way of reducing dropout rates is by identifying at-risk students early. Once a student is identified as at-risk, additional support can be provided to help them stay in school. One emerging method for identifying these at-risk students is predictive analytics. Predictive analytics use a variety of data points to identify when a student is struggling so early intervention can be provided, helping the student stay in school.
One Chinese university utilized predictive analytics in their 8-week online course for graduate students working towards an engineering degree. In this study, researchers used different instructional and feedback methods to determine the impact on student engagement, student performance, and student’s perceptions of the course. The students were split into two groups: a control group and an experimental group. After turning in an assignment, students in the control group were given feedback from the instructor (see section A in the following image). Students in the experimental group were given the instructor’s feedback as well, along with AI performance prediction results, process assessment results, visualizations, and further suggestions (see section b).
At the conclusion of the course, researchers found that providing AI feedback along with the instructor’s feedback improved collaboration and cognitive engagement and created a positive student perception of the course. This experiment showcases predictive analytics power to improve the classroom experience for both students and instructors. The researchers behind the experiment note that predictive analytics can be used to create a feedback loop between students and instructors, allowing instructors to provide additional guidance, reducing the probability of at-risk students.
Personalizing Education with Artificial Intelligence
While learning styles continue to be debated, the positive impact of personalized education is well-documented and widely accepted. However, due to the structure of most modern schools, it is impossible for teachers to personalize education without assistance. Artificial intelligence provides a host of tools to make personalized education a feasible option for teachers all over the world. By implementing artificial intelligence in education, teachers can provide the tools, techniques, and learning materials to help students thrive and meet their educational goals.
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