This article deals with the problem of student dropout during the first year in a higher education institution. To date, no model on a budget has been developed and tested to prevent dropout among Engineering Students. This case study was conducted among first-year students taking evening classes in two practical engineering colleges in Israel. There are three dimensions of the dropout reduction model: social support, institutional support and personal commitment. The results of the intervention had a positive effect on all three dimensions.

The purpose of the research was to identify whether the English language e-classes that are automated and delivered through the Smart Sender platform influence the students’ attendance and procrastination rates, their motivation, time management skills, cognitive processing speed, and satisfaction. The study used qualitative and quantitative methods to monitor students’ attendance and procrastination rates, motivation and engagement, time management skills, thinking speed, and satisfaction. The questionnaire on learning motivation, engagement, and competence, the time management skills test, the mental speed test, and the course satisfaction questionnaire were used to collect data. The focus group discussion questionnaire was used to obtain verbal feedback for the participants. The Smart Sender platform proved effective as an instructional tool for teaching the English Language to students majoring in Philology, International Business, and Law. The automated delivery of the English language e-classes was effective in addressing the issues of dropouts and procrastination in distance learning through automation of the lesson delivery based on the ‘push’ factor. It increased students’ motivation, improves time management skills, and satisfaction. The quantitative findings showed that the students experienced a positive change in attendance, motivation and learning engagement, time management skills, and thinking speed due to the intervention. The students perceived the automated delivery-based approach to language teaching positively. They reported that the delivery approach content met the participants’ expectations and needs. Focus group discussion revealed that the intervention changed their learning behaviour and strategies which were considered the improvements of the quality learning outcomes.

The article aims to develop a machine-learning algorithm that can predict student’s graduation in the Industrial Engineering course at the Federal University of Amazonas based on their performance data. The methodology makes use of an information package of 364 students with an admission period between 2007 and 2019, considering characteristics that can affect directly or indirectly in the graduation of each one, being: type of high school, number of semesters taken, grade-point average, lockouts, dropouts and course terminations. The data treatment considered the manual removal of several characteristics that did not add value to the output of the algorithm, resulting in a package composed of 2184 instances. Thus, the logistic regression, MLP and XGBoost models developed and compared could predict a binary output of graduation or non-graduation to each student using 30% of the dataset to test and 70% to train, so that was possible to identify a relationship between the six attributes explored and achieve, with the best model, 94.15% of accuracy on its predictions.

Students drop out of schools for many reasons, and it has negative effects on the individual and society. This paper reports a study using data published in 2015 from the Educational Longitudinal Study conducted by the National Center for Education Statistics to analyze the influence of parental involvement on low-achieving U.S. students’ graduation rates from high school. Findings indicate that both students and parents share the same perspective on the need for parental involvement in their academic progress. For low-achieving high school students, parental involvement in academic work is a positive factor influencing students’ graduation from high school.

In Austria, segregated German language support classes (GLSC) were introduced in the school year 2018/19 to intensively support students who had previously little or no contact with German, the official language of instruction. These classes have been widely criticised; however, a formal evaluation of their effects has yet to be published. In absence of this evaluation, this article describes the language support model as it currently exists in Austria and reviews existing evidence about its efficacy. The literature review synthesises findings from educational research undertaken in other contexts that offer insight into features of ‘good practice’ in language support models. The article then explores the extent to which GLSC comply with these features. As such, this review allows insights into ways of ensuring students’ language and socio-emotional development – all central aspects of academic success – in language support models. It therefore allows research-informed understanding of the effects of the newly implemented model of German support classes in Austria and makes recommendations for further development.

Academic failure and school dropout, or early school leaving, are two of the situations that most concern countries and educational institutions worldwide, because of their prevalence and also their economic and social implications. Despite this prominent role that academic failure and school dropout have in societies, there seems to be no consensus on the literature on their conceptualization, definition, and relationship. Moreover, it is frequent to observe how both concepts are confused or overlap in the scientific literature and how many authors avoid defining these constructs, using them indistinctly. Therefore, this work analyses whether educational research considers them as two different concepts or if they are used indistinctly. For this purpose, 2,051 keywords from 450 articles were subjected to a systematic review and classified into the Education Resources Information Center (ERIC) thesaurus´ descriptors. The results reveal statistically significant differences in the descriptors according to the type of paper to which they correspond (academic failure or dropout). Thus, academic failure is associated with sociocultural, personal, and academic factors, while dropout is linked to employment and educational trajectories. These differences evidence that, although academic failure and school dropout refer to closely related educational problems, there are remarkable differences between them and between the treatment given to each of them in the scientific literature. Therefore, they should be considered as two different concepts. For all this, keyword analysis has proved to be a relevant element for the study of the structure of knowledge, allowing to clearly establish the differences between the two closely related concepts.

The teaching of experimental sciences in high school contributes to the development of a set of cognitive, methodological, and psychomotor skills among learners. Combining, both theoretical and practical aspects, it involves an important use of scientific experiments in the process of knowledge construction. With the help of appropriate tools that include interviews and observation of teaching practices, data related to the constraints encountered in the implementation of scientific experiments in the high school life sciences classroom was collected as well as proposals of solutions to overcome these constraints. The results show the existence of a set of constraints that oppose the realization of experiments in class. These constraints are not only limited to insufficient or deficient external factors but also to the teachers' relationship to knowledge which influences their choice of teaching activities within a predefined curriculum.

Although central governments, particularly in Latin America and the Caribbean, have defined reducing school dropout rates as a priority, and drawn policies accordingly, there are still young people who do not finish secondary education, and numbers are still alarming. Therefore, it is necessary to observe educational communities and analyze how they interpret and implement guidelines issued by the central government. The following study sought to describe the institutional and teaching practices deployed by four high schools in Valparaíso (Chile) in order to achieve student retention. A qualitative approach was employed. The management team, support professionals, teachers, students, and their families were interviewed. The information gathered was analyzed using the Grounded Theory. As a main finding, establishments use practices such as monitoring attendance, providing support to students facing problematic situations, and encouraging them during class, through a series of strategies. It is recommended that researchers implement this type of methodology for other study objectives, and that the central government consider these results to provide feedback on its policies.

It is known that the COVID-19 pandemic led to learning losses among students both domestically and internationally. Therefore, situational and casual factors were examined to discover and understand them so that learning loss could be reduced or recovered from. This research aimed to: (a) study learning loss situation; and (b) develop and examine the causal model of learning loss among lower secondary school students affected by the pandemic. The sample included 650 Grade 7-9 students selected by multi-stage random sampling. The data was collected using a self-developing questionnaire as a research instrument. The data was analyzed using descriptive statistics, independent samples t-test, ANOVA, and structural equation modeling (SEM) through the LISREL program. The findings were: (a) Lower secondary school students had an average academic achievement learning loss at the moderate level with the highest mean of learning loss in mathematics (M=3.012, SD=1.074), and an average learning characteristics learning loss at the medium level (M=2.824, SD=0.842). Several situational factors had a different effect depending on the school size with a statistical significance of .05.; and (b) the causal model showed the learning loss of grade 7-9 students was consistent with the empirical data (χ2=46.885, df=34, p= .069, GFI=0.991, AGFI=0.964, CFI=0.999, RMSEA=0.024, SRMR=0.014).

School dropout intention and reduced academic achievement are two crucial indicators of school dropout risk. Past studies have shown that school performance plays a mediating role in the models explaining dropout intentions. School burnout and test anxiety have been identified as predictors of both academic performance and school dropout. However, their combined effects on the intention to leave school have not yet been investigated. We aimed to address this gap by exploring the predictors of school dropout intention in a sample of 205 French secondary school students. Structural equation modelling analyses have revealed the specific facets of school burnout (devaluation) and test anxiety (cognitive interference) that explained the school dropout intentions and academic performance. Grade Point Average (GPA) was a mediator of the effects of these variables on the intention to drop out of school. The findings highlight the need to acknowledge assessments as a school stress factor that could contribute to health problems and intentions to drop out of school.