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Studying word order in English sentences is a problem for ESL students whose native languages allow flexible word orders. Developing skills in formulating English sentences often requires trial-and-error process that takes time and requires supervision. Quiz software that is able to analyse students' answers, and give meaningful feedback on mistakes in word order and hints on fixing them allows training without teacher's supervision that greatly enhances the amount of attempts a student can do. In this study, we used CorrectWriting question type for Moodle LMS to create formative and summative quizzes for Russian students learning English as a second language. The experiments show that the students who made more than one attempt of formative quizzes had significantly better learning gains than the students who didn't use formative quizzes or attempted them only once. It also showed vulnerabilities in question design that need to be fixed to utilise software features better in learning process.

Learning in schools has a significant role in improving 21st-century skills, including problem-solving skills. The objective of this research to determine the profile of students' physics problem-solving skills and the implementation of inquiry (free, guided, and structured) learning in senior high school. The study was conducted on 84 students of state senior high school. This type of research was conducted using Descriptive Research Design (DRD). Data collection methods using tests, questionnaire, and interviews. The instrument of research used are (1) instrument tests of physics problem-solving skills, (2) response questionnaire sheets, (3) student and teacher interview sheets. The data obtained were analysed qualitatively descriptive. The results of this study show that only a few students can work on the material using problem-solving strategies of ACCES: (1) Assessing the problem, (2) Create a drawing, (3) Conceptualize the strategy, (4) Execute the solution, and (5) Scrutinize the result, in solving dynamic electricity problems. Implementation of inquiry (free, guided, and structured) learning provided is not ideal so that it causes students to be less active so that problem-solving skills are lacking and no laboratory supports the learning process. Students are not introduced to the existence of a virtual laboratory (i.e. PhET) as a laboratory replacement. So, to improve students' physics problem-solving skills required proper inquiry (free, guided, and structured) learning assisted by PhET.

Lecturer play an important role in the process of planning the learning activities, one of them is in the selection of learning model. This research aims to improve the student activities and learning outcomes in the course of chemistry food materials using problem solving learning models integrated with video media. This research was a classroom action research, which consists of 3 cycles. The participants were students of the chemistry education study program who enrol chemistry food materials courses in the odd semester of academic year 2017/2018, totally 35 people. The data analysis technique is by calculating the average value and classical learning completeness. The data were gathered from test in the end of every cycle. It was found that the student's ability in learning process improved after the implementation of Problem Solving model. It could be seen in the improvement of average score for each test, from 78,81 in cycle I, 80,18 in cycle II to 85,69 in cycle III. In addition, classically learning completeness of students also improved, from 82,86 % in cycle I, 88,57 in cycle II to 100 % in cycle III.

Originality/Value: This study offers a novel combination of customer segmentation, contextual analysis, and reinforcement learning. It demonstrates that this integrated approach can significantly improve recommendation system efficiency, thereby making a valuable contribution to the field of marketing strategies and customer-focused recommendations.

The objectives of this study were to describe the society's empowerment in improving the quality of the learning media, learning process, and learning assessment in school. This research applied qualitative with ethnography research design. The data were collected by in-depth interview, observation, and documentation; while the data analysis technique used was the interactive analysis. The results of the study showed the following conclusions. (1) In order to gain good quality learning, it is a must to prepare a good learning media. The minimum component in developing the learning media (syllabus and lesson plan) must content the learning objectives, learning material, study source, and learning assessment. (2) The learning process must use various ways to encourage students' interest and curiosity, including using various methods, using language styles that are not monotonous, asking questions that guide students' creativity, using multi-method and multimedia, and giving assignments individually and in groups to students. (3) The assessment becomes a very important thing to determine the level of success in the learning that has been done.

The integrated implementation of distance learning online technologies in higher education organizations allows educational organizations to implement educational programs taking into account the individual characteristics of students, in accordance with their educational needs and abilities. Such a personality-oriented education paradigm helps to increase the effectiveness of the learning process, enhance the cognitive activity of students, increase the capabilities of the educational organization in organizing independent work of students. The goal of introducing distance educational online technologies is to increase the effectiveness of training through the implementation of a personality-oriented learning model. The article analyzes the problems of training using remote online technologies, the requirements for the interaction of students and teachers during the educational process, as well as methods for solving these problems. The possibilities of online technologies as an instrument of the educational process, the positive and negative sides of their use are shown.

This research aims to describe the difficulties of the pre-service teacher in designing and implementing inquiry learning in senior high school. A case study design was used for this research. Three pre-service teachers were interviewed and observed to determine the distressing point. This research finds all of the respondents started to design learning inquiry from finding some examples of the inquiry learning process in the internet or senior thesis report and imitated that in their lesson plan. This reflected they had the problem of a doubt what the inquiry process looks like. Along with their self-research about inquiry process illustrations, some of them tried to get the clue in the published article on the internet. It took several weeks to self-analyse what they found on the internet. The majority of problems of this is lack of English understanding. For the implementation process, most of them were able to run the teaching but all of them had a problem with applying the assessment process. Most of them thought the assessment process was just in the formative assessment, not along with the learning process. This research also concludes if they still have much lack of knowledge in desingning inqury learning and lack skill in guiding the students in inquiry learning using guided questions.

The developed software is designed to analyze the semantic compatibility of educational text materials. This need is due to the existing negative trends noted by scientists (didactics, psychologists, neuroscientists) in the mechanism of information perception in the learning process of the modern generation of students. The way to level this tendency in the educational process is to take into account the unconscious patterns of information perception, associated with a gradual increase in its complexity. Semantic compatibility in the developed program is assessed by comparing the thesauri of educational materials, which allows in the future to influence the required degree of increase in their novelty (and, as a consequence, complexity). The work algorithm is formed taking into account the specific variable features of the Russian language. The proposed analytical tool is intended for didactic use, but due to the flexibility of the action algorithms provided by the program, it allows the use of the software product for the analysis of texts for other purposes, for which compatibility is of practical importance.

This study aimed at producing job sheets for basic programming based on performance assessment. The development model used was the ADDIE model which consists of 5 stages: Analysis, Design, Development, Implementation, and Evaluation. The evaluation stage does not stand alone, in which at every stage in the ADDIE model, an evaluation process was conducted. The evaluation stage done here was only a formative evaluation, that is, related to the review process involving experts and a try-out in which the students' responses to the job sheets were elicited to find out the effectiveness of the job sheets. The data were collected using questionnaire. The data collected were reduced and presented. Then the data were analyzed and a conclusion was drawn from the result of the analysis. The result of this study showed that the job sheet for basic programming based on performance assessment has been successfully developed and the attainment level of the job sheet was 80% (a good qualification). This means that it is feasible to be used effectively as media to support the teaching and learning process, especially in practicum activities in basic programming course. The students' response related to the presence of the job sheets was also very good. They were very enthusiastic in following every instruction contained in the job sheets. In other words, there was no deviated reaction/ response at the time of the job sheets review process.

Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of analytical model building and solve associated tasks. Deep learning is a machine learning concept based on artificial neural networks. For many applications, deep learning models outperform shallow machine learning models and traditional data analysis approaches. In this article, we summarize the fundamentals of machine learning and deep learning to generate a broader understanding of the methodical underpinning of current intelligent systems. In particular, we provide a conceptual distinction between relevant terms and concepts, explain the process of automated analytical model building through machine learning and deep learning, and discuss the challenges that arise when implementing such intelligent systems in the field of electronic markets and networked business. These naturally go beyond technological aspects and highlight issues in human-machine interaction and artificial intelligence servitization.