Machine learning methods in predicting the student academic motivation

Academic motivation is closely related to academic performance. For educators, it is equally important to detect early students with a lack of academic motivation as it is to detect those with a high level of academic motivation. In endeavouring to develop a classification model for predicting student academic motivation based on their behaviour in learning management system (LMS) courses, this paper intends to establish links between the predicted student academic motivation and their behaviour in the LMS course. Students from all years at the Faculty of Education in Osijek participated in this research. Three machine learning classifiers (neural networks, decision trees, and support vector machines) were used. To establish whether a significant difference in the performance of models exists, a t-test of the difference in proportions was used. Although, all classifiers were successful, the neural network model was shown to be the most successful in detecting the student academic motivation based on their behaviour in LMS course

Predicting student satisfaction with courses based on log data from a virtual learning environment – a neural network and classification tree model

Student satisfaction with courses in academic institutions is an important issue and is recognized as a form of support in ensuring effective and quality education, as well as enhancing student course experience. This paper investigates whether there is a connection between student satisfaction with courses and log data on student courses in a virtual learning environment. Furthermore, it explores whether a successful classification model for predicting student satisfaction with course can be developed based on course log data and compares the results obtained from implemented methods. The research was conducted at the Faculty of Education in Osijek and included analysis of log data and course satisfaction on a sample of third and fourth year students. Multilayer Perceptron (MLP) with different activation functions and Radial Basis Function (RBF) neural networks as well as classification tree models were developed, trained and tested in order to classify students into one of two categories of course satisfaction. Type I and type II errors, and input variable importance were used for model comparison and classification accuracy. The results indicate that a successful classification model using tested methods can be created. The MLP model provides the highest average classification accuracy and the lowest preference in misclassification of students with a low level of course satisfaction, although a t-test for the difference in proportions showed that the difference in performance between the compared models is not statistically significant. Student involvement in forum discussions is recognized as a valuable predictor of student satisfaction with courses in all observed models

Assessments by Students of the Faculty of Teacher Education on Three Computer Programs Aimed at Child Programmers

Postoje mnogi programi koji mogu pomoći učenicima nižih razreda osnovne škole da se na jednostavan i zanimljiv način upoznaju s osnovnim konceptima programiranja, a neki od njih ne zahtijevaju učenje posebne sintakse koja učenicima u toj dobi čini programiranje teškim. Cilj ovoga rada bio je procijeniti neke programe namijenjene učenicima nižih razreda osnovne škole koji služe za učenje osnovnih koncepata programiranja. Ispitanici su procjenjivali programe Terrapin Logo, Scratch i Kodu. Za potrebe istraživanja kreiran je upitnik koji je služio za ispitivanje stavova ispitanika o navedena tri programa te je davao konačnu ocjenu ispitanika o ispitivanim programima. Dobiveni su odgovori analizirani, a rezultati su pokazali da ispitanici smatraju da su sva tri ispitivana programa adekvatna za poučavanje programiranja učenika nižih razreda osnovne škole, pri čemu je besplatni program Scratch dobio najveću prosječnu ocjenu, odnosno ispitanici su smatrali da je najprikladniji za korištenje u nastavi u nižim razredima osnovne škole.There are many programs which can help pupils in the lower grades of primary school to familiarise themselves with the basic concepts of programming in simple and interesting ways, and some of them do not require learning a specific syntax that makes programming difficult for pupils of that age. The aim of this study was to evaluate some educational programs intended for teaching the basic concepts of programming to pupils in the lower grades of primary school. The participants evaluated Terrapin Logo, Scratch and Kodu programs. For the purpose of this research, a questionnaire was created and used to examine the participants’ attitudes toward these three programs and gave the final participants’ assessment of the programs. The collected data were analyzed and the results showed that the participants considered all three evaluated programs adequate for teaching programming to pupils in the lower grades of primary school. The freeware program Scratch obtained the highest average score, in other words, the participants considered that Scratch was best suited for teaching programming to pupils in the lower grades of primary school

Motor skills in primary education

Za pravilan utjecaj na razvoj sposobnosti, osobina i motoričkih znanja bitno je poznavanje karakteristika rasta i razvoja učenika tijekom primarnog obrazovanja. Različiti autori taj proces rasta i razvoja promatraju kroz različite pristupe. Međutim, bez obzira kojom se klasifikacijom razvojna razdoblja razmatraju, granice između njih ne mogu biti točno određene jer se svako dijete razvija svojstvenom dinamikom. Zato je prijelaz između razdoblja postupan i određen prvenstveno genetskim programom razvoja antropoloških obilježja pojedinog djeteta, a ne godinama njegovog života. Zaključno, redoslijed razvojnih razdoblja jednak je za svu djecu, ali se njihovo pojavljivanje i trajanje vremenski razlikuje. U ovom će radu detaljnije biti opisana motorička znanja koja uz motorička postignuća, funkcionalne sposobnosti te odgojne učinke rada zajedno čine skupinu od pet elemenata ocjenjivanja predmeta tjelesna i zdravstvena kultura.For proper influence on the development of abilities, characteristics and motor skills is essential knowledge of the characteristics of growth and development of students during primary education. Different authors the process of growth and development observed through different approaches. However, no matter which classification developmental period considered, the boundaries between them can not be specific because every child develops the characteristic dynamics. Therefore, the transition between the period of gradual and determined primarily by genetic program of development of anthropological characteristics of individual children, rather than years of his life. In conclusion, the order of the development period is the same for all children, but their occurrence and duration of time is different. This work will be further detailed motor skills with motor achievements, functional abilities and the educational effects of work together form a group of five elements of evaluation items physical educatio

Motor skills in primary education

Za pravilan utjecaj na razvoj sposobnosti, osobina i motoričkih znanja bitno je poznavanje karakteristika rasta i razvoja učenika tijekom primarnog obrazovanja. Različiti autori taj proces rasta i razvoja promatraju kroz različite pristupe. Međutim, bez obzira kojom se klasifikacijom razvojna razdoblja razmatraju, granice između njih ne mogu biti točno određene jer se svako dijete razvija svojstvenom dinamikom. Zato je prijelaz između razdoblja postupan i određen prvenstveno genetskim programom razvoja antropoloških obilježja pojedinog djeteta, a ne godinama njegovog života. Zaključno, redoslijed razvojnih razdoblja jednak je za svu djecu, ali se njihovo pojavljivanje i trajanje vremenski razlikuje. U ovom će radu detaljnije biti opisana motorička znanja koja uz motorička postignuća, funkcionalne sposobnosti te odgojne učinke rada zajedno čine skupinu od pet elemenata ocjenjivanja predmeta tjelesna i zdravstvena kultura.For proper influence on the development of abilities, characteristics and motor skills is essential knowledge of the characteristics of growth and development of students during primary education. Different authors the process of growth and development observed through different approaches. However, no matter which classification developmental period considered, the boundaries between them can not be specific because every child develops the characteristic dynamics. Therefore, the transition between the period of gradual and determined primarily by genetic program of development of anthropological characteristics of individual children, rather than years of his life. In conclusion, the order of the development period is the same for all children, but their occurrence and duration of time is different. This work will be further detailed motor skills with motor achievements, functional abilities and the educational effects of work together form a group of five elements of evaluation items physical educatio

Održavanje skladišta podataka

Skladište podataka je baza podataka koja sadrži povijesne nepromjenjive podatke koji se prikupljaju i analiziraju kao pomoć pri donošenju poslovnih odluka. U radu je dan pregled osnovnih pojmova i razloga nastanka i korištenja skladišta podataka. Također, opisane su razlike u odnosu na klasične, transakcijske baze podataka. Bill Inmon i Ralph Kimball imaju vrlo velik značaj u području oblikovanja skladišta podataka. Inmon je poznat kao ``otac skladištenja podataka'', a Kimball je tvorac dimenzionalnog modeliranja. Njih dvojica imaju različite pristupe oblikovanju skladišta, Inmon se zalaže za pristup razvoju ``od vrha prema dolje'', dok Kimball zastupa pristup ``od dna prema gore''. U radu je dan pregled alata za fizičku realizaciju skladišta podataka te su opisani razlozi i načini nadzora i održavanja skladišta. ETL (Extract-Transform-Load) proces je proces koji označava dohvaćanje podataka, njihovu transformaciju i učitavanje u skladište podataka. Predstavlja najznačajniji dio svakog skladišta podataka. Što se tiče alata, postoje brojni komercijalni i open-source ETL alati, a također možemo i samostalno kodirati ETL proces u proizvoljnom programskom jeziku. Na kraju rada dajemo opis studijskog primjera u kojem demonstriramo kako dizajnirati i implementirati dimenzionalno skladište. Za implementaciju ETL procesa koristimo alat Talend Open Studio.Data warehouse is a database used to collect large amounts of historical data which is then analyzed and used to make better business decisions. This paper gives an overview of basic terms and reasons for the creation and use of data warehouses. Also, we describe the differences between data warehouses and transactional databases. Bill Inmon and Ralph Kimball have made a huge impact in data warehouse modeling techniques. Inmon is known as “father of data warehousing” and Kimball is known for his dimensional modeling technique. The two of them have different approaches to data warehousing, Inmon advocates a “top-down” approach, whereas Kimball suggests a “bottomup” approach. This paper gives an overview of tools used for physical realization of data warehouses. Also, it describes the reasons for monitoring and maintaining a data warehouse and how to do it. ETL is a process of extracting data from source systems, transforming them and loading them into the data warehouse. It is the most important part of building a data warehouse. There are many commercial and open-source ETL tools but there is also the option of hand coding the whole ETL process. At the end of this paper, we give an example in which we demonstrate how to model and implement a data warehouse based on a dimensional model. Our ETL tool of choice is Talend Open Studio

Assessments by Students of the Faculty of Teacher Education on Three Computer Programs Aimed at Child Programmers

Postoje mnogi programi koji mogu pomoći učenicima nižih razreda osnovne škole da se na jednostavan i zanimljiv način upoznaju s osnovnim konceptima programiranja, a neki od njih ne zahtijevaju učenje posebne sintakse koja učenicima u toj dobi čini programiranje teškim. Cilj ovoga rada bio je procijeniti neke programe namijenjene učenicima nižih razreda osnovne škole koji služe za učenje osnovnih koncepata programiranja. Ispitanici su procjenjivali programe Terrapin Logo, Scratch i Kodu. Za potrebe istraživanja kreiran je upitnik koji je služio za ispitivanje stavova ispitanika o navedena tri programa te je davao konačnu ocjenu ispitanika o ispitivanim programima. Dobiveni su odgovori analizirani, a rezultati su pokazali da ispitanici smatraju da su sva tri ispitivana programa adekvatna za poučavanje programiranja učenika nižih razreda osnovne škole, pri čemu je besplatni program Scratch dobio najveću prosječnu ocjenu, odnosno ispitanici su smatrali da je najprikladniji za korištenje u nastavi u nižim razredima osnovne škole.There are many programs which can help pupils in the lower grades of primary school to familiarise themselves with the basic concepts of programming in simple and interesting ways, and some of them do not require learning a specific syntax that makes programming difficult for pupils of that age. The aim of this study was to evaluate some educational programs intended for teaching the basic concepts of programming to pupils in the lower grades of primary school. The participants evaluated Terrapin Logo, Scratch and Kodu programs. For the purpose of this research, a questionnaire was created and used to examine the participants’ attitudes toward these three programs and gave the final participants’ assessment of the programs. The collected data were analyzed and the results showed that the participants considered all three evaluated programs adequate for teaching programming to pupils in the lower grades of primary school. The freeware program Scratch obtained the highest average score, in other words, the participants considered that Scratch was best suited for teaching programming to pupils in the lower grades of primary school

CLASSIFICATION OF ENTREPRENEURIAL INTENTIONS BY NEURAL NETWORKS, DECISION TREES AND SUPPORT VECTOR MACHINES

Entrepreneurial intentions of students are important to recognize during the study in order to provide those students with educational background that will support such intentions and lead them to successful entrepreneurship after the study. The paper aims to develop a model that will classify students according to their entrepreneurial intentions by benchmarking three machine learning classifiers: neural networks, decision trees, and support vector machines. A survey was conducted at a Croatian university including a sample of students at the first year of study. Input variables described students’ demographics, importance of business objectives, perception of entrepreneurial carrier, and entrepreneurial predispositions. Due to a large dimension of input space, a feature selection method was used in the pre-processing stage. For comparison reasons, all tested models were validated on the same out-of-sample dataset, and a cross-validation procedure for testing generalization ability of the models was conducted. The models were compared according to its classification accuracy, as well according to input variable importance. The results show that although the best neural network model produced the highest average hit rate, the difference in performance is not statistically significant. All three models also extract similar set of features relevant for classifying students, which can be suggested to be taken into consideration by universities while designing their academic programs

MODEL NEURONSKIH MREŽA ZA PREDVIĐANJE MATEMATIČKE DAROVITOSTI U DJECE

The aim of this paper was to model a neural network capable of detecting mathematically gifted fourth-grade elementary school pupils. The input space consisted of variables describing the five basic components of a child\u27s mathematical gift identified in the body of previous research. The scientifically confirmed psychological evaluation of gift based on Raven\u27s standard progressive matrices was used at the output. Three neural network models were tested on a Croatian dataset: multilayer perceptron, radial basis, and probabilistic network. The models\u27 performances were measuredaccording to the average hit rate obtained on the test sample. According to the results, the highest accuracy is produced by the radial basis neural network, which correctly recognizes all gifted children. Such high classification accuracy shows that neural networks have the potential to serve as an effective intelligent decision support tool able to assist teachers in detecting mathematically gifted children. This can be particularly useful in schools in which there is a shortage of psychologistsCilj ovoga rada bio je modeliranje neuronske mreže kojom bi se mogla otkriti matematička darovitost u učenika četvrtih razreda osnovnih škola. Ulaz se sastojao od varijabli izvedenih za opis pet osnovnih komponenata matematičke darovitosti u djece, a koje su ustanovljene u prethodnim istraživanjima. Kao izlazni rezultat upotrijebljena je znanstveno potvrđena psihološka evaluacija darovitosti utemeljena u Ravenovim progresivnim matricama. Tri modela neuronskih mreža testirana su na hrvatskim podatcima: višeslojni perceptron, mreža s radijalno zasnovanom funkcijom i probabilistička (vjerojatnosna) mreža. Rad mreža mjeren je u odnosu na prosječnu stopu pogodaka prikupljenih na testnom uzorku. Analiza je pokazala da je najvišu točnost postigla neuronska mreža s radijalno zasnovanom funkcijom, kojom se mogu točno prepoznati sva darovita djeca. Tako visoka točnost u klasifikaciji pokazuje da neuronske mreže imaju potencijal služiti kao efektivan alat inteligentne odluke pomoću kojega bi učitelji mogli otkriti djecu s darovitošću za matematiku. To može biti osobito korisno u školama s manjkom psihologa

MODEL NEURONSKIH MREŽA ZA PREDVIĐANJE MATEMATIČKE DAROVITOSTI U DJECE

The aim of this paper was to model a neural network capable of detecting mathematically gifted fourth-grade elementary school pupils. The input space consisted of variables describing the five basic components of a child\u27s mathematical gift identified in the body of previous research. The scientifically confirmed psychological evaluation of gift based on Raven\u27s standard progressive matrices was used at the output. Three neural network models were tested on a Croatian dataset: multilayer perceptron, radial basis, and probabilistic network. The models\u27 performances were measuredaccording to the average hit rate obtained on the test sample. According to the results, the highest accuracy is produced by the radial basis neural network, which correctly recognizes all gifted children. Such high classification accuracy shows that neural networks have the potential to serve as an effective intelligent decision support tool able to assist teachers in detecting mathematically gifted children. This can be particularly useful in schools in which there is a shortage of psychologistsCilj ovoga rada bio je modeliranje neuronske mreže kojom bi se mogla otkriti matematička darovitost u učenika četvrtih razreda osnovnih škola. Ulaz se sastojao od varijabli izvedenih za opis pet osnovnih komponenata matematičke darovitosti u djece, a koje su ustanovljene u prethodnim istraživanjima. Kao izlazni rezultat upotrijebljena je znanstveno potvrđena psihološka evaluacija darovitosti utemeljena u Ravenovim progresivnim matricama. Tri modela neuronskih mreža testirana su na hrvatskim podatcima: višeslojni perceptron, mreža s radijalno zasnovanom funkcijom i probabilistička (vjerojatnosna) mreža. Rad mreža mjeren je u odnosu na prosječnu stopu pogodaka prikupljenih na testnom uzorku. Analiza je pokazala da je najvišu točnost postigla neuronska mreža s radijalno zasnovanom funkcijom, kojom se mogu točno prepoznati sva darovita djeca. Tako visoka točnost u klasifikaciji pokazuje da neuronske mreže imaju potencijal služiti kao efektivan alat inteligentne odluke pomoću kojega bi učitelji mogli otkriti djecu s darovitošću za matematiku. To može biti osobito korisno u školama s manjkom psihologa