The insertion of Machine Learning (ML) in everyday life demonstrates the importance of popularizing an understanding of ML already in school. Accompanying this trend arises the need to assess the students’ learning. Yet, so far, few assessments have been proposed, most lacking an evaluation. Therefore, we evaluate the reliability and validity of an automated assessment of the students’ learning of an image classification model created as a learning outcome of the “ML for All!” course. Results based on data collected from 240 students indicate that the assessment can be considered reliable (coefficient Omega = 0.834/Cronbach's alpha α=0.83). We also identified moderate to strong convergent and discriminant validity based on the polychoric correlation matrix. Factor analyses indicate two underlying factors “Data Management and Model Training” and “Performance Interpretation”, completing each other. These results can guide the improvement of assessments, as well as the decision on the application of this model in order to support ML education as part of a comprehensive assessment.
This paper introduces constructivist dialogue mapping (CDM), a new type of concept mapping. CDM encodes what people learn during a non-goal directed learning activity. CDM is a practical means to outline the mini theories users fluidly construct as they explore open-ended learning environments. To demonstrate the method, in this paper we use CDM to track how two modelers elaborate understandings during use of a constructionist learning game, Ant Adaptation. Using the method, we show how two users contest and construct their idea of self-organization in ant colonies. The method is rooted in constructionism, constructivism, concept mapping, and conceptual change.
The teaching-learning methodology adopted in the Introduction to Computer Science classes may be a process that makes it difficult to understand the principles of programming language for undergraduate students in Computer Science and related areas, generating high failure and course drop out rates. This paper presents an analysis of the results obtained in the Introduction to Computer Science classes taught in Computer Science and Engineering courses at University of Brasília (UnB). The evaluation questionnaire answered by the undergraduate students in 2017 was analyzed, a validation was performed, and we checked the level of students satisfaction in relation to the evaluated subject and the association among the level of satisfaction, the percentage of practical activities of the discipline, student performance and the level of absenteeism.
The objective of this article is to present the development and evaluation of dETECT (Evaluating TEaching CompuTing), a model for the evaluation of the quality of instructional units for teaching computing in middle school based on the students' perception collected through a measurement instrument. The dETECT model was systematically developed and evaluated based on data collected from 16 case studies in 13 different middle school institutions with responses from 477 students. Our results indicate that the dETECT model is acceptable in terms of reliability (Cronbach's alpha ?=.787) and construct validity, demonstrating an acceptable degree of correlation found between almost all items of the dETECT measurement instrument. These results allow researchers and instructors to rely on the dETECT model in order to evaluate instructional units and, thus, contribute to their improvement and to direct an effective and efficient adoption of teaching computing in middle school.
The teaching of sorting algorithms is an essential topic in undergraduate computing courses. Typically the courses are taught through traditional lectures and exercises involving the implementation of the algorithms. As an alternative, this article presents the design and evaluation of three educational games for teaching Quicksort and Heapsort. The games have been evaluated in a series of case studies, including 23 applications of the games in data structures courses at the Federal University of Santa Catarina with the participation of a total of 371 students. The results provide a first indication that such educational games can contribute positively to the learning outcome on teaching sorting algorithms, supporting the students to achieve learning on higher levels as well as to increase the students' motivation on this topic. The social interaction the games promote allows the students to cooperate or compete while playing, making learning more fun.
Despite the fact that digital technologies are more and more used in the learning and education process, there is still lack of professional evaluation tools capable of assessing the quality of used digital teaching aids in a comprehensive and objective manner. Construction of the Comprehensive Evaluation of Electronic Learning Tools and Educational Software (CEELTES) tool was preceded by several surveys and knowledge obtained in the course of creation of digital learning and teaching aids and implementation thereof in the teaching process. The evaluation tool as such consists of sets (catalogues) of criteria divided into four separately assessed areas - the area of technical, technological and user attributes; the area of criteria evaluating the content, operation, information structuring and processing; the area of criteria evaluating the information processing in terms of learning, recognition, and education needs; and, finally, the area of criteria evaluating the psychological and pedagogical aspects of a digital product. The specified areas are assessed independently, separately, by a specialist in the given science discipline. The final evaluation of the assessed digital product objectifies (quantifies) the overall rate of appropriateness of inclusion of a particular digital teaching aid in the teaching process.
The Lithuanian Informatics Olympiad is a problem solving contest for high school students. The work of each contestant is evaluated in terms of several criteria, where each criterion is measured according to its own scale (but the same scale for each contestant). Several jury members are involved in the evaluation. This paper analyses the problem how to calculate the aggregated score for whole submission in the above mentioned situation. The chosen methodology for solving this problem is Multiple Criteria Decision Analysis (MCDA). The outcome of this paper is the score aggregation method proposed to be applied in LitIO developed using MCDA approaches.
The Lithuanian Informatics Olympiads (LitIO) is a problem solving programming contest for students in secondary education. The work of the student to be evaluated is an algorithm designed by the student and implemented as a working program. The current evaluation process involves both automated (for correctness and performance of programs with the given input data) and manual (for programming style, written motivation of an algorithm) grading. However, it is based on tradition and has not been scientifically discussed and motivated. To create an improved and motivated evaluation model, we put together a questionnaire and asked a group of foreign and Lithuanian experts having experience in various informatics contests to respond. We identified two basic directions in the suggested evaluation models and made a choice based on the goals of LitIO. While designing the model in the paper, we reflected on the suggestions and opinions of the experts as much as possible, even if they were not included into the proposed model. The paper presents the final outcome of this work, the proposed evaluation model for the Lithuanian Informatics Olympiads.
Because of the potential for methodological reviews to improve practice, this article presents the results of a methodological review, and meta-analysis, of kindergarten through 12th grade computer science education evaluation reports published before March 2005. A search of major academic databases, the Internet, and a query to computer science education researchers resulted in 29 evaluation reports that met stringent criteria for inclusion. Those reports were coded in terms of their demographic characteristics, program characteristics, evaluation characteristics, and evaluation findings.
It was found that most of the programs offered direct computer science instruction to North American high school students. Stakeholder attitudes, program enrollment, academic achievement in core courses, and achievement in computer science courses were the most frequently measured outcomes. Questionnaires, existing sources of data, standardized tests, and teacher- or researcher-made tests were the most frequently used types of measures. Based on eight programs that offered direct computer science instruction, the average increase on tests of computer science achievement over the course of the program was 1.10 standard deviations, or the statistical equivalent of 73 out of 100 program participants having shown improvement. Some of the main challenges for the evaluation of computer science education programs are the absence of standardized, reliable, and valid measures of K-12 computer science education and coming to understand the causal links between program activities, gender, and program outcomes.
Currently virtual learning environments (VLEs) and learning objects (LOs) repositories are under active implementation into general education and vocational training system in Lithuania. The article aims to review LOs interoperability standards development tendencies as well as to compare VLEs under existing well-developed pedagogical and technical evaluation frameworks in order to suggest the most suitable one for wider implementation to support active socio-constructivist pedagogies in in-service teacher training and overall in Lithuanian general education and vocational training systems.