Inteligjenca Artificiale në mësimdhënien dhe të nxënit e lëndës së matematikës

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Year-Number: 2021-2/3
Yayımlanma Tarihi: 2021-12-28 23:41:19.0
Language : English
Konu : Mathematics and Science Education
Number of pages: 29-38
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Abstract

Përparimi i shpejtë i teknologjisë, si inteligjenca artificiale (AI) dhe robotika, ka ndikuar në të gjitha industritë, duke përfshirë arsimin. Inteligjenca artificiale po zbatohet me sukses në disa raste arsimore dhe po përmirëson të nxënit dhe zhvillimin e nxënësve, si dhe performancën e mësimdhënësve. Të nxënit e matematikës është konsideruar si një sfidë e madhe për shumë nxënës. Përparimi i teknologjive kompjuterike, në veçanti, inteligjenca artificiale (AI), po ofron një mundësi për të përballuar këtë problem duke diagnostikuar problemet e të nxënit të nxënësve individualisht dhe duke ofruar mbështetje të personalizuar për të maksimizuar performancën e tyre në të nxënit e lëndës së matematikës. Qëllimi i këtij artikulli është të ofrojë një përmbledhje të njohurive të Inteligjencës Artificiale (AI) që po përdoren në metodologjinë e mësimdhënies bashkëkohore në lëndën e matematikës. Rezultatet nga studimi eksplorues kanë potencialin për të ofruar njohuri të rëndësishme për AI në mësimdhënien dhe të nxënit e lëndës së matematikës. Këto gjetje mund të informojnë hetime të mëtejshme për të mbështetur dizajnin e të nxënit dhe vlerësimin në progresionet të të nxënit të bazuara në teknikat e inteligjencës artificiale.

Keywords

Abstract

The rapid advancement of technology, such as artificial intelligence (AI) and robotics, has affected all industries, including education. Artificial intelligence is being successfully applied in some educational cases and is improving student learning and development as well as teacher performance. Learning math is considered a great challenge for many students. The advancement of computer technologies, in particular, artificial intelligence (AI), is providing an opportunity to tackle this problem by diagnosing students' learning problems individually and providing personalized support to maximize their learning performance. mathematics. The purpose of this article is to provide an overview of the Artificial Intelligence (AI) knowledge being used in contemporary teaching methodology in mathematics. The results from the exploratory study have the potential to provide relevant knowledge about AI in the teaching and learning of the subject of mathematics. These findings may inform further investigations to support learning design and assessment in learning progression based on artificial intelligence techniques.

Keywords


  • Mathematics refers to learning content which uses symbolic language to represent concepts suchas number, quantity, space and structure. The subject of mathematics has been identified as acomplex and challenging task that aims to enhance students' competence in problem solving.Several previous studies have reported that students generally find it difficult to complete mathtasks, especially those that need to be solved in multiple steps. Therefore, researchers have madeefforts to develop different learning strategies and tools to improve learning outcomes inmathematics. They have also noted the importance of identifying factors that affect studentperformance in learning mathematics, such as insufficient prior knowledge and lack ofpersonalized support for students in the individual form. Meanwhile, the advancement of artificialintelligence (AI) has provided a tool to address these problems. (Bray & Tangney, 2017; Civil &Bernier, 2006; Paras, 2001; Stephan, et al., 2015; Acharya, 2017; Davadas & Lay, 2017; Chen, Xie, & Zou, 2020).

  • Hwang et al. (2020) have identified several AI roles in education, as an intelligent teacher,caregiver, learning tool and partner, as well as educational policy-making advisor (Hwang, Xie,Wah, & Gasevic, 2020). Regarding the role of the intelligent teacher, the use of AI technologieshelps to simulate the intelligence of teachers to provide personalized guidance, feedback or supportto students during the learning process, has been demonstrated by several researchers. Forexample, Hwang and other authors (2020) developed an adaptive learning system for math courses,taking into account students' cognitive and affective performance individually (Hwang, Xie, Wah, & Gasevic, 2020).

  • Researchers have also shown that in the 21st century, in addition to imparting knowledge, it isimportant to encourage students to think at the highest level, such as questioning skills, criticalthinking, problem solving and creative thinking, therefore mathematics is the foundation of theseskills. Several previous studies have highlighted that in mathematics education, it is important tosupport students to learn to think critically, communicate with others, solve problems and buildknowledge, while also providing them with mathematical concepts and methods. (Demir & Basol,2014 ). Some researchers have further pointed out that the use of AI technologies to analyse thelearning status or behaviours of students enables the development of intelligent teachers who areable to provide individually effective interventions for students to improve their studentperformance. their learning and motivation. For example, one study by Xie et al. (2017) used thegenetic algorithm to implement a personalized e-learning system to provide personalizedcurriculum development recommendations for students by promoting their learning performance.(Xie, et al., 2017). Another example is the use of AI technologies (e.g., unsupervised machinelearning method) in the development of student models for predicting students' commitment or individual learning status in mathematics. (Tang, Chang, & Hwang, 2021).

  • In 2013, Arnau et al. designed an intelligent tutorial system for learning the arithmetic andalgebraic way of solving word problems. Hypergraph-based problem solver (HBPS) was able toreinforce the translation of a problem into algebraic language or provide an arithmetic way ofsolving a problem. The system uses hypergraphs, easy for users to understand, to present theanalytical reading of a particular problem, as well as to present a solution process, with manyalternative solutions. HBPS also provides automatic feedback and suggestions when the usermakes a mistake (Arnau, Arevalillo-Herráez, Puig, & González-Calero, 2013). Also in 2010, Bealet al. conducted three studies with high school students to evaluate AnimalWatch, an intelligentarithmetic and fractional learning system. The software relied on artificial intelligence algorithmsto provide personalized support for students individually. AnimalWatch features word problems,from the easiest to the most challenging, designed to train the user in basic computational andfractional skills. The AI is able to assess the student's abilities for each topic and respectively giveuseful suggestions or move on to a new mathematical topic. Overall, the results of the studiesencouraged the hypothesis that software can be a useful and motivating educational tool (Beal,Arroyo, Cohen, Woolf, & Beal, 2010). Matsuda and VanLehn (2005) proposed an intelligentteaching system to improve the teaching of the geometry theorem that is proved by construction.Advance Geometry Tutor starts with a certain theorem of the geometry problem and thecorresponding figure. The user is allowed to draw line segments in the figure to prove the theorem.The teacher gives comments and instructions that the student should follow through the messageswindow. The postulate browser window contains a list of postulates that can be used by the studentfor authentication. Finally the student can see the whole procedure that must be followed step bystep to reach the test in the conclusion part (Matsuda & VanLehn, 2005). Another AI service isthe MathTutor system, which provides step-by-step suggestions when solving problems usingteacher instruction tracking. These teachers are able to assess students' problem-solving behaviouras well as provide multi-strategy problem-solving guidance. MathTutor, which is an open accesswebsite, also provides detailed performance data for each student, available to teachers or parents.Feng et al. (2008) proposed an intelligent learning system designed to predict students' math skills.The ASSISTment system is a combination of computer-based learning and standardized tests. Ifthe student solves the given problem correctly, a new problem is given. If the student answersincorrectly, the system offers a small tutorial session, where the student is given the problemdivided into subproblems to progressively reach the solution. According to researchers, the modelcan even do a standardized test (Feng, Beck, Heffernan, & Koedinger, 2008). Craig et al. (2013)proposed ALEKS, a web-based learning system with artificial intelligence components, as amethod of intervening in after-school settings to improve mathematical skills. The intelligenttutoring system administers a test to assess the student's initial state of knowledge. The student cansee a summary of his / her learning progress in each topic on a board. The student can then choosehow to proceed from a list of types of problems he / she is ready to learn (Craig, et al., 2013).Methods and Materials

  • o Rule-based reasoning: is a special type of reasoning that uses "if-else" statements. Intelligentteaching systems that adopt rule-based reasoning use logical connections such as AND, OR, NOT,etc. to form logical functions. The essential components of these systems are the rule base, theinference engine, which uses the knowledge provided by the rule base, working memory, whereknown facts are stored, and the mechanism of explanation (Prentzas & Hatzilygeroudis, 2007).

  • o Case-based reasoning: uses examples of problems encountered in the past to solve new problems. Case-based reasoning systems consist of the following parts (Alves, Amaral, & Pires, 2008):

  • o Neural networks: represent a different approach to artificial intelligence inspired by biologicalneural networks. Network activation flows from the input layer through the hidden (middle) layer,then to the output layer. Each link is related to its weight. The weights of a neural network aredetermined by a training process with empirical data. The performance of neural networks is also sensitive to the number of neurons (Ding, Li, Su, Yu, & Jin, 2013).

  • o Constraint-based modelling: constraint-based model tutors use student errors to construct astudent model represented as a set of constraints violated or not. Each constraint consists of three components (Ma, Adesope, Nesbit, & Liu, 2014):

  •  Personalized learning: Managing a classroom of many students makes personalized learningalmost impossible. However, AI can provide a level of differentiation that adapts learning specifically to a student's strengths and weaknesses individually (Marr, 2018).

  •  Teacher help: Teachers not only teach; they also spend hours evaluating documents and preparingfuture lessons. However, some tasks, such as writing on paper, can be performed by robots, givingteachers a lighter workload and more flexibility to focus on other things (Nelson, 2018). Machinescan now evaluate multiple choice tests and are close to being able to manually evaluate written answers (Marr, 2018).

  •  Teacher teaching: Artificial intelligence makes available to teachers complete information at anytime of the day. They can use this information to further their education in such things as learning foreign languages or mastering complex programming techniques (Nelson, 2018).

  •  Connecting everyone: Because AI is computer based, it can connect with different classes aroundthe world, fostering greater collaboration, communication and collaboration between schools and students (Nelson, 2018).

  •  Ster Thinkster Math: Thinkster Math is a learning application that combines true mathcurriculum with a personalized teaching style. She uses artificial intelligence and machinelearning in their math teacher app to visualize how a student is thinking while working tosolve a problem. This allows the teacher to quickly discern the areas of thinking and logicof a student that have caused them to stumble and help them through immediate and personalized feedback (Sennar, 2019).

  •  Rain Brainly: Brainly is a platform where students can ask homework questions and getautomatic answers, verified by their peers. The site even allows them to collaborate andfind solutions themselves. Mind uses machine learning algorithms to filter out the unwanted result (Sennar, 2019).

  •  Ent Content Technologies, Inc.: Content Technologies, Inc. (CTI) is an AI company thatuses Deep Learning to create personalized learning tools for students, such as Just TheFacts 101, where teachers import curricula into a CTI engine. The CTI machine then usesalgorithms to create personalized texts and subjects based on core concepts. Cram 101 isanother AI-enhanced example, where any textbook can be turned into a smart study guide,delivering small-sized content that is easy to learn in no time. It even generates multiplechoice questions, saving students time and helping them learn more effectively. (Turbot, 2018).

  •  MATHiaU: Similar to Thinkster Math, MATHiaU offers AI-based teaching tools forhigher education students who feel overlooked in the classroom by educators. The app isguided by each student's unique learning process, keeps them aware of their daily progress, and helps teachers tailor lessons to meet each student's specifics (Couture, 2018).

  •  Netex Learning: Netex Learning allows teachers to design and integrate curricula acrossa range of digital platforms and devices. The easy-to-use platform allows them to createpersonalized student content that can be published on any digital platform. Teachers alsoreceive tools for video conferencing, digital discussions, personalized assignments andlesson analysis that show visual representations of each student's personal growth (Sennar, 2019).

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