Artificial Intelligence in Education

Elementary school students' awareness of the use of artificial intelligence chatbots in violence prevention education in South Korea: a descriptive study

“…However, the results of a study on the use of a chatbot for foreign language education conducted in South Korea showed that students had increased confidence, found their classes to be fun, and wanted to continue learning [ 3 ]. These results support those of a study by Holmes [ 30 ] that showed that chatbots were an artificial intelligence technology with strong educational potential since they can provide quick and appropriate information through direct verbal and written interactions.…”

Use of the Tensorflow Framework to Support Educational Problems: A Systematic Mapping

“…After a brief reading in the 32 abstracts, we classified them in six main categories as shown in Table 3. (Malekian et al, 2020), (Vijayalakshmi & Venkatachalapathy, 2019), , (Boncea et al, 2019), (Pablo, 2020), (Cheng & Zhang, 2020), (Aveleyra et al, 2018), (Tsiakmaki & Kostopoulos, 2020), (Czibula et al, 2019), , (Monllaó Olivé, et al, 2020), (Chunqiao et al, 2018), (Preuveneers et al, 2020), (Kőrösi & Farkas, 2020), (Injadat et al, 2020), (Qiu et al, 2019) Representation Learning (Zhang et al, 2019) Knowledge (Lee & Yeung, 2019), (Yang & Cheung, 2018), (Sha & Hong, 2017) Tracing Pedagogical Data Analytics (Guo & Zeng, 2020), (Hernández-Blanco, 2019), (Gudivada, et al, 2016) Decision Support System (Gutu-Robu et al, 2018), (Stoica, et al, 2019), (Holmes, 2020), (Moore et al, 2019), (Pensel & Kramer, 2020) Evaluation (Doleck et al, 2020) As expected, most of the papers (20) published belong to the Student Modeling category. Basically, the general focus represents cognitive aspects of student activities, such as analyzing students' performance, isolating underlying misconceptions, representing students' goals and plans, identifying prior and acquired knowledge, maintaining an episodic memory, and describing personality characteristics (Bakhshinategh et al, 2017).…”

“…Neural networksupervised (Chunqiao et al, 2018) To predict student study failure risk in early time and improve the efficiency and effectiveness of early warning education Neural network (Holmes, 2020) To introduce the Artificial Intelligence in Education approach, its set of technologies and a field of inquiry General (Moore et al, 2019) To generate personalized homework assignments for students using behavioural cloning of teacher activity Neural network (Preuveneers et al, 2020) To observe the behavior of the audience and keeping the participants engaged Edge-based multi-modal engagement solution (Pensel & Kramer, 2020) to forecast of the study success in selected STEM disciplines (computer science, mathematics, physics, and meteorology), solely based on the academic record of a student so far, without access to demographic or socioeconomic data random forest, support vector machine, multilayer perceptron, long short-term memory networks (Yang & Cheung, 2018) To propose an automatic and effective way to preprocess the heterogeneous features into the deep knowledge tracing model Neural network and tree based classifiers (Kőrösi & Farkas, 2020) To predict student performance at the end of the Massive Open Online Course using directly raw log data Recurrent neural network (Injadat et al, 2020) To predict the students' performance at two stages of course delivery (20% and 50%) K-nearest neighbor, random forest, support vector machine, multinomial logistic regression, naive Bayes, and neural network (Sha & Hong, 2017) To model complex representations of student knowledge and predict future performances of students.…”

“…In the literature, it is possible to find some systematic reviews/mappings regarding Educational Data Mining (EDM), such as Bakhshinategh et al (2017), Hernández-Blanco et al (2019, Holmes(2020); however, they do not mention use of TensorFlow framework in the context. Thus, this paper highlights the challenges that researchers of the Computer Science teaching degree have about this study area.…”

Artificial intelligence and machine learning

“…The fact that a new generation of robots will coexist with humans should be taken into account in legislation. In the article [4], [5], [6], [8], [10], [11], [12] they talk about the prospects of using AI in education, various teaching methods are being developed and AI is being actively used, and they also see prospects for the development of AI in education, unlike the article [13], which states that schools and universities are relatively less priority goals in the development of new systems based on artificial intelligence than, for example, medical diagnostics or individual transport. The article [9] says that the use of artificial intelligence in medicine will create many application opportunities to improve patient care, provide real-time data analysis and ensure continuous monitoring of patients.…”