scholarly journals Personalized and Adaptive Learning

2021 ◽  
pp. 17-34
Author(s):  
Deborah L. Taylor ◽  
Michelle Yeung ◽  
A. Z. Bashet
Keyword(s):  
Artificial Intelligence ◽  
Student Success ◽  
Student Satisfaction ◽  
Student Learning ◽  
Adaptive Learning ◽  
Personalized Learning ◽  
Learning Approach ◽  
Individualized Learning ◽  
Student’S Performance ◽  
Increasing Student Learning

AbstractPersonalized and adaptive learning has been touted to be one of the most promising emerging tools for increasing student learning and student success. Yet, the terms are neither precise nor clearly defined at this time, thus making it difficult for institutions of higher education to adopt and implement a learning approach using technology that is in its infancy and not clearly understood by those who will be utilizing it. One goal of this chapter is to define adaptive and personalized learning as it is used at this time in the hopes that as the technology evolves the promise of increased student learning can come to fruition. Adaptive learning personalizes learning by continuously evaluating each student’s performance in real time and creating an ever-changing individualized learning pathway as directed by artificial intelligence and machine learning, thus increasing learning and student satisfaction.

A SMARTPHONE-BASED ADAPTIVE LEARNING APPROACH TO ENHANCE STUDENTS’ LEARNING OUTCOMES IN ENGLISH SUBJECT

2021 ◽  
Vol 8 (2) ◽  
Author(s):  
Farhanirahma ◽  
Lidiyatul Izzah ◽  
Muhamad Sofian Hadi
Keyword(s):  
Student Learning ◽  
Learning Outcomes ◽  
Adaptive Learning ◽  
Test Group ◽  
Student Learning Outcomes ◽  
Learning Approach ◽  
Learning Approaches ◽  
Mean Values ◽  
Significance Level ◽  
Post Test

The purpose of this study is to improve student learning outcomes through a smartphone-based adaptive learning approach to 28 students from the 11th grade students in the 2020/2021 academic year. It is important to consider the educational context when evaluating the barriers to adopting adaptive learning approaches on digital platforms. The method used in this study is a quantitative method, everything observed was measured and converted into numbers so that statistical analysis techniques were possible. The author chose  a pre-experimental design with a pre-test post-test group design, in which a group of subjects is taken from a certain population and performed in a pre-test and then undergoes treatment one after another. After the treatment, the person received a posttest to measure the learning outcomes of the group. The grades given have the same weight. The difference between the results of the pretest and the post-test shows the results of the treatment performed. The results of this study were analyzed using the t-test by comparing the mean values of the pre-test and post-test. The results showed that the t-observation value (7.8) was higher than the t-table value (1.70562) at the 5% significance level. It can be concluded that the learning approach adaptive smartphone-based improves student learning outcomes in English subjects.

A tale of two courses: challenging Millennials to experience culture through film

2017 ◽  
Vol 10 (2) ◽  
pp. 41-57
Author(s):  
Katie Kirakosian ◽  
Virginia McLaurin ◽  
Cary Speck
Keyword(s):  
Social Science ◽  
Learning Styles ◽  
Student Success ◽  
Student Satisfaction ◽  
Student Learning ◽  
Cognitive Process ◽  
American University ◽  
Science Educators

In this article, we discuss how adding a final film project to a revised ‘Culture through Film’ course led to deeper student learning and higher rates of student success, as well as increased student satisfaction. Ultimately, we urge social science educators to include experiential projects in their courses that connect to all learning styles. Such projects should also challenge students to ‘create’, a task that requires generating ideas, planning and ultimately producing something, which, according to Bloom’s revised taxonomy, engages students in the highest cognitive process (Anderson and Krathwohl 2000). Although this class focused on the intersections of culture and film and was taught at an American university, we believe these lessons apply more broadly.

scholarly journals Findings From an Examination of a Class Purposed to Teach the Scientific Method Applied to the Business Discipline

10.28945/4794 ◽  
2021 ◽  
Vol 18 ◽  
pp. 161-172
Author(s):  
Nicole A. Buzzetto-Hollywood
Keyword(s):  
Higher Education ◽  
Student Success ◽  
General Education ◽  
Student Satisfaction ◽  
Student Learning ◽  
Scientific Method ◽  
Scientific Reasoning ◽  
Student Perception ◽  
The United States ◽  
Future Research

Aim/Purpose: This brief paper will provide preliminary insight into an institutions effort to help students understand the application of the scientific method as it applies to the business discipline through the creation of a dedicated, required course added to the curriculum of a mid-Atlantic minority-serving institution. In or-der to determine whether the under-consideration course satisfies designated student learning outcomes, an assessment regime was initiated that included examination of rubric data as well as the administration of a student perception survey. This paper summarizes the results of the early examination of the efficacy of the course under consideration. Background: A small, minority-serving, university located in the United States conducted an assessment and determined that students entering a department of business following completion of their general education science requirements had difficulties transferring their understanding of the scientific method to the business discipline. Accordingly, the department decided to create a unique course offered to sophomore standing students titled Principles of Scientific Methods in Business. The course was created by a group of faculty with input from a twenty person department. Methodology: Rubrics used to assess a course term project were collected and analyzed in Microsoft Excel to measure student satisfaction of learning goals and a student satisfaction survey was developed and administered to students enrolled in the course under consideration to measure perceived course value. Contribution: While the scientific method applies across the business and information disciplines, students often struggle to envision this application. This paper explores the implications of a course specifically purposed to engender the development and usage of logical and scientific reasoning skills in the business discipline by students in the lower level of an bachelors degree program. The information conveyed in this paper hopefully makes a contribution in an area where there is still an insufficient body of research and where additional exploration is needed. Findings: For two semesters rubrics were collected and analyzed representing the inclusion of 53 students. The target mean for the rubric was a 2.8 and the overall achieved mean was a 2.97, indicating that student performance met minimal expectations. Nevertheless, student deficiencies in three crucial areas were identified. According to the survey findings, as a result of the class students had a better understanding of the scientific method as it applies to the business discipline, are now better able to critically assess a problem, feel they can formulate a procedure to solve a problem, can test a problem-solving process, have a better understanding of how to formulate potential business solutions, understand how potential solutions are evaluated, and understand how business decisions are evaluated. Conclusion: Following careful consideration and discussion of the preliminary findings, the course under consideration was significantly enhanced. The changes were implemented in the fall of 2020 and initial data collected in the spring of 2021 is indicating measured improvement in student success as exhibited by higher rubric scores. Recommendations for Practitioners: These initial findings are promising and while considering student success, especially as we increasingly face a greater and greater portion of under-prepared students entering higher education, initiatives to build the higher order thinking skills of students via transdisciplinary courses may play an important role in the future of higher education. Recommendations for Researchers: Additional studies of transdisciplinary efforts to improve student outcomes need to be explored through collection and evaluation of rubrics used to assess student learning as well as by measuring student perception of the efficacy of these efforts. Impact on Society: Society needs more graduates who leave universities ready to solve problems critically, strategically, and with scientific reasoning. Future Research: This study was disrupted by the COVID-19 pandemic; however, it is resuming in late 2021 and it is the hope that a robust and detailed paper, with more expansive findings will eventually be generated.

Artificial Intelligence Applications with e-Learning System for China’s Higher Education Platform

2021 ◽  
Author(s):  
Xiaoran Fu ◽  
K. Lokesh Krishna ◽  
R. Sabitha
Keyword(s):  
Artificial Intelligence ◽  
Higher Education ◽  
Student Learning ◽  
Learning Style ◽  
Adaptive Learning ◽  
Teaching Quality ◽  
Learning System ◽  
Learning Context ◽  
E Learning ◽  
Student Learning Style

Artificial Intelligence (AI) assisted educational institutions extensively utilize electronic learning context to guarantee improved teaching and learning experiences accompanied by educational activities. E-learning or online learning plays a significant role in Chinese higher education. There is a challenge to implement e-learning in China’s higher education to improve course resources, student learning style prediction, teaching quality, and service support. Hence in this paper, Artificial Intelligence based Efficient E-learning Framework (AI-EELF) has been proposed to overcome the challenges faced by China’s higher education while implementing e-learning modules. The collected student data can be efficiently utilized and exploited to progress in an adaptive learning environment. The proposed AI-EELF method introduces multiple learning models to enhance teaching quality and predict the student learning style. The experimental results show that the proposed AI-EELF achieves high performance, prediction ratio in determining students’ learning style and improves teaching quality compared to other existing methods.

Virtual Screening Meets Deep Learning

2018 ◽  
Vol 15 (1) ◽  
pp. 6-28 ◽  
Author(s):  
Javier Pérez-Sianes ◽  
Horacio Pérez-Sánchez ◽  
Fernando Díaz
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Virtual Screening ◽  
Great Increase ◽  
New Drugs ◽  
Learning Approach ◽  
Screening Strategies ◽  
Computer Aided ◽  
Recent Developments

Background: Automated compound testing is currently the de facto standard method for drug screening, but it has not brought the great increase in the number of new drugs that was expected. Computer- aided compounds search, known as Virtual Screening, has shown the benefits to this field as a complement or even alternative to the robotic drug discovery. There are different methods and approaches to address this problem and most of them are often included in one of the main screening strategies. Machine learning, however, has established itself as a virtual screening methodology in its own right and it may grow in popularity with the new trends on artificial intelligence. Objective: This paper will attempt to provide a comprehensive and structured review that collects the most important proposals made so far in this area of research. Particular attention is given to some recent developments carried out in the machine learning field: the deep learning approach, which is pointed out as a future key player in the virtual screening landscape.

Robot Teaching, Pedagogy, and Policy

2020 ◽  
pp. 787-803
Author(s):  
Elana Zeide
Keyword(s):  
Artificial Intelligence ◽  
Analytical Methods ◽  
Personalized Learning ◽  
Educational Process ◽  
Learning Systems ◽  
Policy Decisions ◽  
Public Discussion ◽  
Teaching Pedagogy ◽  
Do So

This chapter looks at the use of artificial intelligence (AI) in education, which immediately conjures the fantasy of robot teachers, as well as fears that robot teachers will replace their human counterparts. However, AI tools impact much more than instructional choices. Personalized learning systems take on a whole host of other educational roles as well, fundamentally reconfiguring education in the process. They not only perform the functions of robot teachers but also make pedagogical and policy decisions typically left to teachers and policymakers. Their design, affordances, analytical methods, and visualization dashboards construct a technological, computational, and statistical infrastructure that literally codifies what students learn, how they are assessed, and what standards they must meet. However, school procurement and implementation of these systems are rarely part of public discussion. If they are to remain relevant to the educational process itself, as opposed to just its packaging and context, schools and their stakeholders must be more proactive in demanding information from technology providers and setting internal protocols to ensure effective and consistent implementation. Those who choose to outsource instructional functions should do so with sufficient transparency mechanisms in place to ensure professional oversight guided by well-informed debate.

Design of English reading and learning management system in college education based on artificial intelligence

2021 ◽  
pp. 1-10
Author(s):  
Fen Zhang ◽  
Min She
Keyword(s):  
Artificial Intelligence ◽  
Model Performance ◽  
College Education ◽  
Personalized Learning ◽  
Learning System ◽  
Model Function ◽  
English Reading ◽  
Function Modules ◽  
Learning Platforms ◽  
Learning Management

English reading learning in college education is an efficient means of English learning. However, most of the current English reading learning platforms in colleges and universities only put different English books on the platform in electronic form for students to read, which leads to blindness of reading. Based on artificial intelligence algorithms, this paper builds model function modules according to the needs of English reading and learning management in college education and implements system functions based on artificial intelligence algorithms. Moreover, according to the above design principles of personalized learning model and the characteristics of personalized network learning, this paper designs a personalized learning system based on meaningful learning theory. In addition, this article verifies and analyzes the model performance. The research results show that the model proposed in this paper has a certain effect.

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