Ľubomír Šnajder

Contribution: We present a framework for teachers to investigate the relationships between attributes of students’ solutions in the process of problem solving or computational thinking. We provide visualization and evaluation techniques to find hidden patterns in the students’ solutions which allow teachers to predict the specific behavior of students or to prevent some student mistakes or misconceptions in advance or further pedagogical intervention. Background: Formal concept analysis is a method of unsupervised Machine Learning that applies mathematical lattice theory to organize data based on objects and their shared attributes. Several fuzzy extensions of formal concept analysis have a great potential to visualize and evaluate students’ solutions, to categorize the solutions into overlapping biclusters (formal concepts) or to generate the attribute implications between extracted attributes. Research Question: Does formal concept analysis describe the various solutions and the relationships between the extracted attributes of students’ solutions in the educational and computational thinking game Light-Bot? Methodology: Targeting the evaluation of 64 students’ solutions in the Light-Bot game, we construct the formal contexts of the extracted attributes. We apply formal concept analysis to construct the concept lattices from two binary formal contexts and to generate attribute implications and their fuzzy counterparts to find the dependencies between the extracted attributes. Findings: The results of our paper provide a description of various students’ solutions which are visualized in the concept lattices. 1) Regarding the concept lattice of binary formal contexts, we obtained the characterization of the largest biclusters which includes a description of the largest group of similar solutions. 2) The attribute implications mainly reveal the characterization of similar solutions, e.g., with a higher count of executed commands in solutions. 3) Using fuzzy attribute implications, we obtained the characterization of solutions with unnecessary commands, going out of the game area, or using indirect recursion.

Data analytics plays a significant role within the context of the digital business landscape, particularly concerning online sales, aiming to enhance understanding of customer behaviors in the online realm. We review the recent perspectives and empirical findings from several years of scholarly investigation. Furthermore, we propose combining computational methods to scrutinize online customer behavior. We apply the decision tree construction, GUHA (General Unary Hypotheses Automaton) association rules, and Formal concept analysis for the input dataset of 9123 orders (transactions) of sports nutrition, healthy foods, fitness clothing, and accessories. Data from 2014 to 2021, covering eight years, are employed. We present the empirical discoveries, engage in a critical discourse concerning these findings, and delineate the constraints inherent in the research process. The decision tree for classification of the year’s fourth quarter implies that the most important attributes are country, gross profit category, and delivery. The classification of the morning time implies that the most important attributes are gender and country. Thus, the potential marketing strategies can include heterogeneous conditions for men and women based on these findings. Analyzing the identified groups of customers by concept lattices and GUHA association rules can be valuable for targeted marketing, personalized recommendations, or understanding customer preferences.

Active learning, represented by inquiry-based science education (IBSE) strategies, is considered essential for students to develop skills and knowledge to prepare for the challenges of the 21st century world. The success of IBSE, and the resulting development of inquiry skills in particular, can be enhanced by various factors. This study is focused on the synergetic effect of the implementation of IBSE through well-designed inquiry activities across STEM-related disciplines, enhanced by digital technologies and formative assessment tools, delivered by teachers educated in this field. The corresponding research based on a quasi-experimental design evaluated the effect on the development of inquiry skills that were identified before and after a period of consistent implementation of IBSE, using a written test of inquiry skills as the main research instrument. The research findings on the sample of 2307 upper secondary school students confirmed a low initial level of inquiry skills, however a statistically significant improvement in students’ inquiry skills with medium size effect was identified. The detailed analysis shows the largest impact in the skill of determination of accuracy and statistically significant differences between genders without practical importance, however no difference was identified with regard to the number of inquiry activities undertaken.

Information about the paper titled "FORMATIVE ASSESSMENT STRATEGIES FOCUSED ON DEVELOPING METACOGNITIVE SKILLS" at IATED Digital Library

Bádateľsky orientované vzdelávanie (BOV) patrí v poslednom období k najčastejšie skloňovaným pojmom v súvislosti s inováciou prírodovedného vzdelávania. Cieľom BOV je okrem konceptuálneho porozumenia aj rozvoj žiackych zručností realizovať bádanie a vyhodnocovať jeho výsledky. Prezentovaný výskum je zameraný na diagnostikovanie aktuálnej úrovne rozvoja vybraných bádateľských zručností žiakov gymnázia. Vychádzajúc z dostupných testov bol na základe klasifikácie bádateľských zručností vytvorený test bádateľských zručností. Testové úlohy určené na posúdenie úrovne zručnosti plánovať postup experimentu (identifikovať premenné a ich vzťah), transformovať výsledky do grafu, určovať vzťahy medzi premennými, identifikovať možné zdroje chýb a obhajovať výsledky a argumentovať, sú vsadené do matematického, fyzikálneho alebo informatického kontextu. Test bol zodpovedaný vzorkou 751 žiakov 1. a 2. ročníka niekoľkých gymnázií na Slovensku. Kvantitatívna analýza výsledkov testovania ukázala nízku priemernú úspešnosť žiakov v celom teste (32,5 %) ako aj v jednotlivých testových úlohách pohybujúcu sa približne v rozmedzí 8–50 %. Zo štatistického testovania vyplynulo, že medzi výsledkami žiakov 1. a 2. ročníka nebol významný rozdiel, zatiaľ čo výsledky chlapcov boli lepšie ako výsledky dievčat. Podrobná kvalitatívna analýza odhalila mnohé nedostatky, ktoré sa najvýraznejšie prejavili v oblasti analýzy a interpretácie výsledkov a žiackych argumentačných zručností.

In the paper we present the partial results of a qualitative research achieved in the project Innovation efficiency methods of teaching mathematics, physics and informatics (VEMIV). The project is aimed at developing inquiry skills of pupils and conceptual comprehension of the subject matter. In the first part we describe basic characteristics of inquiry-based education. In the second part we present two methodologies of teaching informatics. The first methodology is primarily focused on scientific research methods viable in school informatics. In the second one, we focus primarily on the content of school informatics. The methodologies were implemented and commented by teachers from partner grammar schools. At the end of both methodologies we summarize and analyze the results of inquiry-based education according to the presented methodologies. Our findings are supported by the results of pupils’ works, the results of concepTest and evaluation feedback from teachers. In conclusion, we present recommendations for the implementation and evaluation of inquirybased informatics education.