scholarly journals Student Performance on the BDSI for Basic Data Structures

2022 ◽  
Vol 22 (1) ◽  
pp. 1-34
Author(s):  
Kevin C. Webb ◽  
Daniel Zingaro ◽  
Soohyun Nam Liao ◽  
Cynthia Taylor ◽  
Cynthia Lee ◽  
...  
Keyword(s):  
Student Performance ◽  
Conceptual Understanding ◽  
Data Structures ◽  
Strong Evidence ◽  
Basic Data ◽  
Concept Inventory ◽  
Using Data

A Concept Inventory (CI) is an assessment to measure student conceptual understanding of a particular topic. This article presents the results of a CI for basic data structures (BDSI) that has been previously shown to have strong evidence for validity. The goal of this work is to help researchers or instructors who administer the BDSI in their own courses to better understand their results. In support of this goal, we discuss our findings for each question of the CI using data gathered from 1,963 students across seven institutions.

INCREASED STUDENT PERFORMANCE ON PHYSICS CONCEPT INVENTORY TEST AFTER STUDENT-CENTRED APPROACH IN UNIVERSITIES OF LATVIA

2021 ◽  
Author(s):  
Ilva Cinite ◽  
◽  
Girts Barinovs ◽  
Keyword(s):  
Active Learning ◽  
Student Performance ◽  
Conceptual Understanding ◽  
Physics Education ◽  
Teaching Approach ◽  
Concept Inventory ◽  
Test Results ◽  
Widespread Application ◽  
Force Concept Inventory ◽  
Force Concept

Education research has repeatedly shown that active learning in physics is pedagogically more efficient than traditional lecture courses. Widespread application of the active learning is slowed down by the lack of data on the performance of the active learning in widely varying circumstances of different educational systems. We measured the level of understanding of basic physics concepts using Force Concept inventory for students who enrol at different universities in Latvia in calculus-based and non-calculus-based groups and compared the student performance to the pre-test results elsewhere in the world. We measured the growth of concept inventory test results and studied the dependence of the growth on the teaching approach used by university lecturers. About 450 undergraduate students from 12 groups of science and engineering courses taught by 8 lecturers were involved in the study at three universities in Latvia. The Force Concept Inventory multiple-choice test was translated to Latvian and used for pre-/post-tests. The pre-test results showed that the maximum of the distribution of correct answers for non-calculus groups is around 20%, which is the value obtained by the random guessing of test answers, whereas the pre-test results of calculus-based groups was about 50% of correct answers. The test score after taking post-test confirmed that the growth of students’ tests results is closely related to the teaching approach chosen by lecturer, showing that in order to provide physics graduates with a good conceptual understanding of physics, student centred teaching approach was crucial. The use of concept inventories in undergraduate physics education to measure the progress of learning appears to be particularly important in the current situation with a small number of students in physics and a critically small number of future physics teachers, when efficiency of teaching is of crucial importance. Keywords: STEM education quality, conceptual understanding, student-centred approach

scholarly journals Enhanced conceptual understanding in first year mechanics through modelling

2016 ◽  
pp. 22-26
Author(s):  
David Sands ◽  
Abigail L Marchant
Keyword(s):  
Student Performance ◽  
Conceptual Understanding ◽  
Concept Inventory ◽  
First Year ◽  
Mathematical Equations ◽  
Third Law ◽  
The Impact ◽  
Structured Approach ◽  
Conceptual Difficulties ◽  
Force Concept

As part of the National HE STEM programme, we have developed and implemented a modelling curriculum in first year mechanics to overcome well known conceptual difficulties. By modelling, we mean more than just the development of mathematical equations to describe the evolution of a physical system; we also mean the use of multiple representations both to understand the problem at hand as well as to develop a solution. We have developed a structured approach to both teaching and assessing the use of such representations through the ACME protocol: Assess the problem, Conceptualise the Model, and Evaluate the solution. This paper describes the implementation of this protocol within a conventional lecture setting during a single semester of the 2011-12 academic session and demonstrates the impact on conceptual understanding of 42 students though pre-course and post-course testing using the Force Concept Inventory (FCI). Detailed analysis shows that on virtually every question in the FCI student performance improved, with questions 4 and 15, relating to Newton’s third law, showing especially large gains. The average FCI score rose from 17.7 (out of 30) to 22.5, with the distribution of post-instruction scores being statistically significantly different (p=0.0001) from the distribution of pre-instruction scores.

Basic Data Structures — III. Records

Microcomputer ◽  
1977 ◽  
pp. 408-425
Author(s):  
Kenneth L. Bowles
Keyword(s):  
Data Structures ◽  
Basic Data

scholarly journals Using Data Mining for Improving Education of University Students – A Survey

2018 ◽  
Vol 6 (9) ◽  
pp. 78-83 ◽  
Author(s):  
K. P. S. D. Kumarapathirana
Keyword(s):  
Data Mining ◽  
Academic Success ◽  
Student Retention ◽  
Student Performance ◽  
Poor Performance ◽  
Academic Behavior ◽  
System Logs ◽  
Using Data ◽  
Visualization Techniques ◽  
The University

Data mining combines machine learning, statistical and visualization techniques to discover and extract knowledge. Student retention is an indicator of academic performance and enrolment management of the university. Poor student retention could reflect badly on the university. Universities are facing the immense and quick growth of the volume of educational data stored in different types of databases and system logs. Moreover, the academic success of students is another major issue for the management in all professional institutes. So the early prediction to improve the student performance through counseling and extra coaching will help the management to take timely action for decrease the percentage of poor performance by the students. Data mining can be used to find relationships and patterns that exist but are hidden among the vast amount of educational data. This survey conducts a literature survey to identify data mining technologies to monitor student, analyze student academic behavior and provide a basis for efficient intervention strategies. The results can be used to develop a decision support system and help the authorities to timely actions on weak students.

scholarly journals Analisis Pemahaman Konsep Mahasiswa Pendidikan Fisika Universitas Sriwijaya pada Materi Gravitasi Newton dengan Menggunakan NGCI Dan CRI Termodifikasi

2019 ◽  
Vol 3 (1) ◽  
pp. 65
Author(s):  
Anita Yuza Rahayu ◽  
Syuhendri Syuhendri ◽  
Ida Sriyanti
Keyword(s):  
Conceptual Understanding ◽  
Physics Education ◽  
Gravitational Force ◽  
Basic Research ◽  
Concept Inventory ◽  
Newtonian Gravity ◽  
Response Index ◽  
Analysis Methods ◽  
Qualitative Technique ◽  
Descriptive Qualitative

This research aims to analyze about conceptual understanding and misconceptions on material Newtonian Gravity of students physics education Sriwijaya University. Data collected by using test NGCI (Newtonian Gravity Concept Inventory), CRI (Certainty of Response Index), and Interview to discribed types of conceptual understanding students�. Analysis methods data used Descriptive qualitative technique. Based on the analysis CRI, this research find 28,51 % student understand the concept, 4,68 % understand the concept but not sure , 27,9% misconception, and 25,62 % not understand the concept. The most misconception occurs in sub concept the relations of mass to the gravitational force that is 49,65 %. This research can be used for basic research increase student conceptual understanding

scholarly journals Performance Analysis and Prediction Student Performance to build effective student Using Data Mining Techniques

2019 ◽  
Vol 3 (2) ◽  
pp. 10
Author(s):  
Ardalan Husin Awlla
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Student Performance ◽  
Fraud Detection ◽  
Classification Model ◽  
Data Mining Techniques ◽  
Incipient Stage ◽  
The Everyday ◽  
Using Data

In this period of computerization, schooling has additionally remodeled itself and is not restrained to old lecture technique. The everyday quest is on to discover better approaches to make it more successful and productive for students. These days, masses of data are gathered in educational databases, however it stays unutilized. To be able to get required advantages from such major information, effective tools are required. Data mining is a developing capable tool for examination and expectation. It is effectively applied in the field of fraud detection, marketing, promoting, forecast and loan assessment. However, it is in incipient stage in the area of education. In this paper, data mining techniques have been applied to construct a classification model to predict the performance of students.

PROBLEMS OF CREATING A LIVING STANDARDS MODEL

2021 ◽  
Vol 4 (1) ◽  
pp. 9-14
Author(s):  
Abdujabbor Abidov ◽  
Keyword(s):  
Big Data ◽  
Data Structures ◽  
Poverty Line ◽  
Poverty Measurement ◽  
Living Standards ◽  
Standard Of Living ◽  
Formal Modeling ◽  
Digital Platforms ◽  
Communication Models ◽  
Using Data

This article is devoted to the development of a model for determining the standard of living of the population. The problems of using data warehouses, communication models of e-government that form the basis of digital platforms, big data, issues of the digital economy, the choice of data structures, methods of formal modeling of relationships are also considered.As a result, a model was developed using the poverty criteria set out in the Poverty Measurement Toolkit when determining the international poverty line.

scholarly journals Challenges Assessing the Conceptual Understanding of Students With Disabilities in Statistics

2019 ◽  
Vol 42 (3) ◽  
pp. 175-185 ◽  
Author(s):  
Ibrahim H. Dahlstrom-Hakki ◽  
Zachary G. Alstad
Keyword(s):  
Students With Disabilities ◽  
Student Performance ◽  
Conceptual Understanding ◽  
Language Processing ◽  
Conceptual Knowledge ◽  
Autism Spectrum ◽  
Sentence Length ◽  
Generalized Linear Mixed Effects ◽  
K 12 ◽  
The Impact

Standardized assessment of content knowledge for STEM (Science, Technology, Engineering, Mathematics) topics is pervasive in both K-12 and postsecondary institutions. Yet, most instruments are developed with little to no validation for students with learning disability (LD), attention deficit hyperactivity disorder (ADHD), and autism spectrum disorder (ASD). In this study, we evaluate the effectiveness of new test instruments designed to assess conceptual understanding of statistics content and the extent to which construct-irrelevant factors, such as language processing, influence the performance of students with disabilities. Generalized linear mixed-effects modeling was used to identify the factors that were predictive of student performance. Results indicate that the average sentence length in word problems was uniquely predictive of student performance on emerging assessments of conceptual understanding. The results provide new evidence of the barriers facing students with disabilities on emerging tests of conceptual knowledge. A general framework for measuring the impact of these barriers and the effectiveness of accommodations is discussed.

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