Development of the scoring mechanism for the concept map based intelligent knowledge assessment system

Anohina-Naumeca, Alla; Strautmane, Maija; Grundspeņķis, Jānis

doi:10.1145/1839379.1839446

Cited by 6 publications

(3 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The demonstrated knowledge of the learners was used to examine the extent of achieving the learning outcomes. The research in [35] perused the technique of scoring the students' knowledge through parameters like linkages of concepts established in the concept maps and patterns of correct and semi-correct propositions established for making the linkages. However, no specific standard is established to rate students' knowledge through their developed concept maps [28].…”

Section: Concept Mappingmentioning

confidence: 99%

Cognitive Learning Analytics Using Assessment Data and Concept Map: A Framework-Based Approach for Sustainability of Programming Courses

2020

View full text Add to dashboard Cite

Students of initial level programming courses generally face difficulties while learning the programming concepts. The learning analytics studies, in these courses, are mostly anecdotal on the aspect of assessment as less or no attention is given to assess learning at various cognitive levels of specific concepts. Furthermore, the existing work reflects deficiencies in examining the effect of learners’ cognitive performance on subsequent stages of the course. This gap needs to be addressed by introducing more granular and methodical approaches of cognitive analysis for sustaining the programming courses effectively in computer science and associated disciplines. In this article, a framework-based approach is proposed for cognitive learning analytics on the concepts taught in initial level programming courses. The framework serves as a platform that provides structure to the concept data using the technique of concept mapping and examines learners’ cognitive propagation on related concepts using assessment data. Learners’ performance prediction has been examined on relatively higher-level programming concepts through the metrics established from the cognitive maps of learners, acquired by deploying the related layers of framework. Overall maximum prediction accuracy range obtained was 64.81% to 90.86%, which was better than the prediction accuracies presented in most of the related studies.

show abstract

Section: Concept Mappingmentioning

confidence: 99%

Cognitive Learning Analytics Using Assessment Data and Concept Map: A Framework-Based Approach for Sustainability of Programming Courses

2020

View full text Add to dashboard Cite

show abstract

“…The system can operate a) in mode of knowledge selfassessment allowing a student to assess his/her knowledge level and to learn more about a specific topic in case of incomplete knowledge, or b) in mode of knowledge control intended for the determination of students' knowledge level by a teacher [28].…”

Section: Overview Of Ikasmentioning

confidence: 99%

Conception of the Animated Interface Agent for the Concept Map Based Intelligent Knowledge Assessment System

Anohina-Naumeca¹,

Lukašenko²,

Skripkins³

2011

Scientific Journal of Riga Technical University. Computer Sciences

Self Cite

View full text Add to dashboard Cite

-The paper presents the conception of the animated interface agent for the concept map based assessment system. The agent is being developed with an aim to solve problems related to rare use or users' unawareness of functional capabilities of the system. The conception consists of agent's goal, functions, inputs, outputs, embodiment, and properties. It is based on the interface agent characteristics and design requirements summarized in the paper, as well as analysis of system needs.

show abstract

“…A lot of studies in pedagogy are devoted to the issue of assessing knowledge. In particular: monitoring the quality of education (Cherednichenko and Yangolenko [7], He and He [16], Igbape and Idogho [19], Leontev et al [21], Li et al [22], Muhd Nor et al [25], Qin et al [30], Sorour et al [49], Wei [54], Zhi and Nan [56] and others); development of modern innovative technologies that are included in the knowledge assessment system (Anohina-Naumeca, Strautmane and Grundspenkis [2], Anohina-Naumeca and Grundspenkis [1], Gierłowski and Nowicki [13], Grundspenkis [14], Schmuck, Sima and Szöllosi [41], Szöllosi, Sima and Schmuck [50] and others); the use of a multi-point scale for assessing knowledge, abilities, and skills (Bespalko [5], Linn [23] and others); theoretical approaches to the assessment of students' knowledge, their development and improvement (Clotfelter, Ladd and Vigdor [8], Falchikov and Boud [11], Falchikov and Goldfinch [12], Host, Regnell and Wohlin [17], Hwang and Chang [18], Newble and Jaeger [27], Osadchyi et al [28], Rust, Price and Berry [39], Scouller [42], Topping [53], Wiliam et al [55] and others); evaluation of test results in an adaptive automated testing system, taking into account the ambiguity of the formulations of answers (Barker [3], Phankokkruad and Woraratpanya [29], Rudinskiy [38] and others). In [6] we substantiated the structural model of the neuro-fuzzy system of professional selection of students for training in IT specialties by studying the psychological characteristics, personal qualities and factual knowledge, skills and abilities of students as a unity of fuzzy and stochastic data base of t...…”

Section: Introductionmentioning

confidence: 99%

Simulation of intellectual system for evaluation of multilevel test tasks on the basis of fuzzy logic

et al. 2021

View full text Add to dashboard Cite

The article describes the stages of modeling an intelligent system for evaluating multilevel test tasks based on fuzzy logic in the MATLAB application package, namely the Fuzzy Logic Toolbox. The analysis of existing approaches to fuzzy assessment of test methods, their advantages and disadvantages is given. The considered methods for assessing students are presented in the general case by two methods: using fuzzy sets and corresponding membership functions; fuzzy estimation method and generalized fuzzy estimation method. In the present work, the Sugeno production model is used as the closest to the natural language. This closeness allows for closer interaction with a subject area expert and build well-understood, easily interpreted inference systems. The structure of a fuzzy system, functions and mechanisms of model building are described. The system is presented in the form of a block diagram of fuzzy logical nodes and consists of four input variables, corresponding to the levels of knowledge assimilation and one initial one. The surface of the response of a fuzzy system reflects the dependence of the final grade on the level of difficulty of the task and the degree of correctness of the task. The structure and functions of the fuzzy system are indicated. The modeled in this way intelligent system for assessing multilevel test tasks based on fuzzy logic makes it possible to take into account the fuzzy characteristics of the test: the level of difficulty of the task, which can be assessed as “easy”, “average", “above average”, “difficult”; the degree of correctness of the task, which can be assessed as “correct”, “partially correct”, “rather correct”, “incorrect”; time allotted for the execution of a test task or test, which can be assessed as “short”, “medium”, “long”, “very long”; the percentage of correctly completed tasks, which can be assessed as “small”, “medium”, “large”, “very large”; the final mark for the test, which can be assessed as “poor”, “satisfactory”, “good”, “excellent”, which are included in the assessment. This approach ensures the maximum consideration of answers to questions of all levels of complexity by formulating a base of inference rules and selection of weighting coefficients when deriving the final estimate. The robustness of the system is achieved by using Gaussian membership functions. The testing of the controller on the test sample brings the functional suitability of the developed model.

show abstract

Development of the scoring mechanism for the concept map based intelligent knowledge assessment system

Cited by 6 publications

References 8 publications

Cognitive Learning Analytics Using Assessment Data and Concept Map: A Framework-Based Approach for Sustainability of Programming Courses

Cognitive Learning Analytics Using Assessment Data and Concept Map: A Framework-Based Approach for Sustainability of Programming Courses

Conception of the Animated Interface Agent for the Concept Map Based Intelligent Knowledge Assessment System

Simulation of intellectual system for evaluation of multilevel test tasks on the basis of fuzzy logic

Contact Info

Product

Resources

About