The increasing interest in educational data mining makes it a new growing research area. Educational data mining also referred to as “EDM” is defined as the area of scientific inquiry centered around the development of techniques for making discoveries within the sets of data found in learning environment, and using those techniques to understand the students and the learning environment. It is a very powerful tool to reveal hidden patterns and precious knowledge, which otherwise may be difficult to establish and comprehend using traditional statistical methods. This paper introduces educational data mining, its advantages and limitation. discusses educational data mining techniques by conducting step by step processes also identified the
What student demographics and Student Support Services program services at Johnston Community College can be used to predict academic success? 2. What student demographics and Student Support Services program services at Johnston Community College can be used to predict persistence? Significance of the Study Academic success and student persistence will be the primary focus of this study. Identifying services that predict student academic success and persistence among TRIO student is important for staff and higher education leaders at Johnston Community College.
STUDENT MODELLING BASED ON E-LEARNING K.karthik1, Abhay Kumar2, Dheeraj Kumar3, and Krishna Kumar4 1 Department of computer science engineering, 2,3Final year IT 4Final year CSE Aarupadai Veedu Institute of Technology Chennai Abstract. We utilize the student assessment module to evaluate the student performance through profession and their skill means to form student model and realize personalized learning using the model. The study presents a student assessment and modeling system, an essential component of a distributed intelligent e-learning environment. To make the e-learning environment intelligent and adaptive to each individual student. SAM models the ability of the student more accurately by taking the student’s careless
SURVEY OF LEARNING ANALYTICS BASED ON PURPOSE AND TECHNIQUES FOR IMPROVING STUDENT PERFORMANCE Dr.Suchithra R Department of Computer Science, Jain University Bengaluru email@example.com V.Vaidhehi Department of Computer Science, Christ University Bengaluru firstname.lastname@example.org Nithya Easwaran Iyer Department of Computer Science, Sri Vani International School, Bengaluru email@example.com ABSTRACT I Learning Analytics is a process to analyze the learners which improves the educational performance. Learning Analytics also helps the higher educational institutions to improve the educational practices and techniques. This paper provides a detailed survey of the current research activities conducted in the
One of the areas where the application of learning analytics is needed is open and distance learning. Learners in open and distance learning perform learning activities and a set of interactions electronically and leave behind some electronic traces after each action. These traces are a prominent source of data for enhancing learners' academic performance, estimating prospective academic steps, improving open and distance learning platforms, and testing teaching competencies as well. Analyzing large amounts of data from learners containing millions of numbers, using traditional methods makes it challenging to get answers to some questions. Hence, the use of learning analytics seriously supports the decision makers and practitioners in achieving the desired objectives.
• To create a module that will compute the students’ grade based on input data. • To create a module that will secure and maintain the integrity of data. 7.0 Scope of the Project The proposed system is composed of the main modules, namely the registration module where students and lecturers are entered, the subject module, where the lecturers can enters the mark of the student for each grade components, and grade computation module, where the grade of the student is calculated based on the input marks for each grade components. 8.0 Client
Lok David (2008), investigated the relationship between individuals‟ achievement strategy adopted in academic setting, their Big Five personality, and their academic achievement. This study also examined whether achievement strategy groups (i.e., optimism, defensive pessimism, self-handicapping, and learned helplessness) could be identified in the Hong Kong education context, and how these achievement strategies may be related to personalities. Methods: Participants were three groups of students at different educational level (lower secondary school, upper secondary school, and university undergraduate). They completed questionnaires that assess their achievement strategy in academic context, their personality dimension, and their achievement outcome. Results: The present study found consistent patterns of relationship between personality, achievement strategy, and academic achievement across the three educational levels.
Since this problem I am seeking to solve is deriving directly from students, I have chosen to include information about two student development theories. If one can understand the theories and how they explain a student 's thought process, decision making, an often actions, then solutions can be presented with these theories in mind. Student development theories can offer a variety of insights once understood. One can determine where a student has developed their own opinions and values. Student development theories can also help one understand how students change in college, and what impact college has on students.
Also, formative assessments give our students evidence of their current progress to actively manage and adjust their own learning. This also provides our students the ability to track their educational goals. In addition, formative assessments give us the ability to provide constant feedback to our students. This allows our students to be part of the learning environment and to develop self-assessment strategies that will help with the understanding of their own thought process. Remarkably, Black and Wiliam (1998) conducted an extensive research study involving over 250 studies to ascertain whether or not formative assessment could be shown to raise levels of attainment in the classroom.
A STUDY OF RELATIONSHIP BETWEEN FRUSTRATION AND SOCIO-ECONOMIC FACTORS AMONG UNDERGRADUATE STUDENTS OF DIFFERENT STREAMS Anis Jahan, Associate Professor, Department of Education, Aligarh Muslim University, Aligarh, U.P., India (firstname.lastname@example.org), Mob.963965354 Abstract Socio economic status (SES) is one of the most widely used contextual variables in educational research. SES as a variable is mainly used to find its correlation with various variables such as anxiety, stress, complex, study habits and academic achievement. Socio-economic status refers to a specific hierarchy in social positions which can be used to illustrate a person’s overall social status. It can be indicated by a number of sub concepts such as, level of education, profession, economic position, lifestyle, health, aspiration, use of gadgets, services and leisure facilities that the family enjoys. The present research is conceived and formulated on a very wide canvas of adolescents studying in undergraduate classes in India in context of their socioeconomic status and its relation with frustration.