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Sd Mathematics Learning Application
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Department Of Mathematics
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Gwo-Jen HwangGwo-Jen Hwang SciProfiles Scilit Preprints.org Google Scholar * and Yun-Fang TuYun-Fang Tu SciProfiles Scilit Preprints.org Google Scholar
Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taipei City 106335, Taiwan
Learning Resources Mini Muffin Match Up Math Activity Set
Submission received: February 15, 2021 / Reviewed: March 5, 2021 / Accepted: March 6, 2021 / Published: March 10, 2021
Learning mathematics can be a big challenge for many students. The development of computer technologies, particularly artificial intelligence (AI), offers an opportunity to address this problem by diagnosing individual students’ learning problems and providing individualized support to optimize their learning performance in mathematics courses. However, there is a lack of reviews from different perspectives, which would help researchers, especially novice researchers, get a comprehensive picture of research on AI in mathematics education. To this end, the aim of this research is to conduct a bibliometric mapping analysis and systematic review to examine the role and research trends of AI in mathematics education by searching for relevant articles published in quality journals published by the Social Science Citation Index. (SSCI) from the Web of Science (WOS) database. Furthermore, referring to the technology-based learning model, there are several dimensions of AI in mathematics education research, including: B. Application domains, participants, research methods, adopted technologies, research questions and roles of AI and mentioned and co-. B. Reference relationships are taken into account. Accordingly, AI developments in mathematics education research are reported and potential research topics for future research are recommended.
Mathematics refers to learning content that uses symbolic language to represent concepts such as number, size, space, and structure [1]. Mathematics teaching is recognized as a complex and challenging task that aims to develop learners’ ability to solve problems [2]. Several previous studies have indicated that students generally find it difficult to solve mathematical problems, especially those that require multiple steps [3, 4]. Therefore, researchers have made efforts to develop various learning strategies and tools to improve student learning outcomes in mathematics [1]. He pointed out the importance of identifying factors that affect students’ learning performance in mathematics, such as: b. Lack of adequate prior knowledge and personal support for individual students [5, 6].
Meanwhile, the development of artificial intelligence (AI) provides a way to overcome these problems [7]. AI refers to a field of computer science research that aims to develop computer systems that can perform tasks that require human intelligence, such as: b. Visual and linguistic recognition, inferences and decision making [8]. A number of previous applications have demonstrated the potential to apply AI in education, particularly to assist students in completing complex or challenging tasks [9, 10]. For example, Chen and Liu [11] developed a personalized computer-based system for solving mathematical problems, and it was effective in improving students’ learning performance and attitude.
Maths Book Std. 2
Researchers have identified various roles of AI in education, such as intelligent tutor, tutor, learning tool and partner, as well as advisor for educational policy making [12]. Regarding the role of the intelligent tutor, several researchers have demonstrated the use of artificial intelligence technologies to simulate teacher knowledge to provide guidance, feedback, or personal support to individual students in the learning process. For example, Hwang et al. [13] developed an adaptive learning system for mathematics courses considering the cognitive and affective performance of individual students.
To examine research roles and trends in mathematics education (AIME), the present study conducted a bibliometric mapping analysis and systematic review to analyze published studies in the WOS database according to the technology-based learning model proposed by Lin and Hwang. . [14] to answer the following research questions:
The development of various information, communication and computer technologies has opened up new opportunities to improve teaching and learning; In particular, the rapid development of AI allows computer systems to act more like a tutor than traditional teaching systems [7]. AI technologies can be used to analyze student learning, including interaction content, learning behavior, test scores, and learning outcomes, to provide immediate support or feedback to individual students, as well as to provide suggestions to teachers to improve content and teaching strategies [15] ]. Scholars [11, 12, 15] have found that facilitating personalized learning is one of the main goals of artificial intelligence in education (AIED). Zawacki-Richter et al. [16] reviewed AIED in higher education studies published between 2007 and 2018 and concluded that AI has been applied in various application areas, particularly in computer science, science, technology, engineering and mathematics.
In the 21st century, researchers have found that in addition to presenting information, it is important to promote higher-order thinking skills such as questioning, critical thinking, problem-solving, and creative thinking skills; Mathematics is the basis of these skills [17]. Several previous studies have emphasized the importance of helping students think critically, communicate with others, solve problems, and construct information while introducing mathematical concepts and methods in mathematics education [18, 19]. Several researchers [7, 16, 20] have suggested that the use of artificial intelligence technologies to analyze students’ learning status or behavior enables the development of intelligent teachers who can provide effective interventions to individual students to improve their learning performance. and motivation. For example, one of the studies [21] used a genetic algorithm to implement a personalized e-learning system to provide personalized curriculum sequence recommendations to individual learners to boost their learning performance.
Kisi Kisi Matematika Kelas 6 Sd
Additionally, the integration of AI technologies in educational environments allows computer learning systems to take on the role of tutors, tools or intelligent students, as well as in policy making [12, 20]. For example, some previous studies used AI technologies to simulate teachers’ behavior in detecting students’ learning problems and provide content and personalized learning paths, and provide suggestions or guides to individual students in mathematics courses [22, 23, 24]. A recent review study on technology-enhanced adaptive/personalized learning [25] showed that the development and popularization of AI has gradually achieved the main goal of technology-enhanced learning, namely, providing a personalized or adaptive learning environment to improve students’ learning performance. . For example, some studies have suggested that providing contextual personalization in intelligent tutoring systems (ITS) can increase learners’ contextual interest and performance in mathematical tasks [26, 27]. Another example is the use of AI technologies (e.g., unsupervised machine learning approach) in developing student models to predict individual learning engagement or individual student status in mathematics courses [28].
The literature shows that AI is becoming increasingly influential in mathematics education. Scholars have found that analyzing publications in a particular area can provide researchers in that field with valuable information about trends or potential research questions [12, 16, 25]. In the past three decades, researchers have mainly focused on AIED trends and issues [7, 12], AI in e-learning [29], AI in higher education [16], AI in medical education [30] and AI focused applications in engineering [31]. Scholars have found that mathematics education is very important in the 21st century because it is closely related to the development of students’ problem-solving skills and extracurricular experiences [32, 33, 34]. Gallagher et al. [32] conducted a literature review on adaptive mathematics education from 1975 to 2014 and showed that technology can support students in learning mathematics knowledge and skills and stimulate their creativity. However, a review for AIME has not yet been conducted.
To address this issue, this research aims to use bibliometric mapping analysis to analyze AIME research, including commonly used keywords, journals, papers, and most contributing authors. Additionally, we conduct a systematic review and discuss application domains, sample groups, research methods, AI roles, and dimensions of AI algorithms.
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