Learning Itineraries to Work Mathematic Probability with Future Teachers in an Online Scenario with Deck.Toys Tool

The work of Probability from the Compulsory Secondary Education stage and during the Baccalaureate is not generally contextualised and is, mainly, based on the rote learning of formulas. Therefore, when students arrive at university, a significant lack of knowledge related to the calculation of probabilities is evident. Teachers have to advocate for classroom strategies that help students to achieve lasting and contextualized learning and, even more, in areas such as Probability. This paper presents the design of a didactic proposal based on the use of gamified learning itineraries utilizing Deck.Toys digital tool for the learning of Probability in a sample of students of the Primary Education Degree who worked on an online environment. For this analysis, the outcomes obtained in two tests, initial and final, are collected in an experimental group that has used the tool and compared with those of a control group that worked in a traditional way. Moreover, the data of a survey of the evaluation of the user experience was also analysed. The results gained have been very satisfactory, the tests of comparison of means in the post-test shows a significant difference of 2.704 points more in the experimental group, taking into account that both groups were homogeneous. Likewise, the results of the satisfaction survey have been positive in terms of improving the understanding of both the procedures and the concepts involved on time management since students have been able to work at their own rhythm in an efficient way.El trabajo de Probabilidad desde la etapa de Educación Secundaria Obligatoria y durante el Bachillerato no está generalmente contextualizado y se basa principalmente en el aprendizaje memorístico de fórmulas. Por tanto, cuando los estudiantes llegan a la universidad, se evidencia una importante falta de conocimientos relacionados con el cálculo de probabilidades. El profesorado debe abogar por estrategias en el aula que ayuden al estudiantado a lograr un aprendizaje duradero y contextualizado, más aún en áreas como la probabilidad. En este artículo se presenta el diseño de una propuesta didáctica basada en el uso de itinerarios de aprendizaje gamificados utilizando la herramienta digital Deck.Toys para el aprendizaje de la Probabilidad en una muestra de alumnos del Grado de Educación Primaria que trabajaban en un entorno online. Para el análisis, se recogen los resultados de dos pruebas, pretest y postest, en el grupo que ha utilizado la herramienta y en el que no forma online y se comparan los resultados obtenidos. Además, también se analizaron los datos de una encuesta de evaluación de la experiencia de usuario. Los resultados obtenidos muestran que la diferencia de medias en el postest es significativa de 2.704 puntos más en el grupo experimental, con un tamaño de efecto grande, aunque los grupos eran homogéneos. Asimismo, los resultados de la encuesta de satisfacción han sido positivos en cuanto a la mejora en la comprensión de los procedimientos y conceptos implicados y en la gestión del tiempo ya que han podido trabajar a su propio ritmo de forma eficiente

Analysis of the use of automatic judges in computer programming classes in vocational education

The goal of this thesis is to analyse the use of automatic judges in the teaching of Computer Programming in Vocational Training programs, in a sample of secondary schools in Catalonia and Spain. We review the academic literature on automatic judges and describe their history and the different services that are currently available. Through surveys to teachers and students from Vocational Training centres, we have collected information about the tools in use. We classify twelve of them according to features that we found to be relevant to the teachers we surveyed. Using the collected data, we study the reasons in favour and against automatic judges, as well as the level of familiarity of active teachers with those tools. We identify some discrepancies between teacher's expectations and actual experiences of teachers who have adopted them. We use students' responses to derive statistics about their satisfaction, and to detect differences in the attitude of those who use judges in class and those who don't with respect to the subject of programming. In order to detect any effects on learning, we use three Bebras challenges to evaluate the competence of algorithmic and computational thinking. No difference in the ability of students to complete these challenges has been observed, but a difference in how willing they are to work on them has been detected. The effect is contrary to the one originally hypothesised, which leads to some interesting questions for further study

Recall and post-trip evaluation of tourist destinations: the effects of travel order

Samira Zare explored the role of heuristic biases involved in recall and evaluation of tourists' destinations. She found that the first and last cities in a sequence are recalled and evaluated better than the middle destinations. She provided a foundation for future studies about order effects in tourism and hospitality

Predicting student performance in interactive online question pools using mouse interaction features

Modeling student learning and further predicting the performance is a well-established task in online learning and is crucial to personalized education by recommending different learning resources to different students based on their needs. Interactive online question pools (e.g., educational game platforms), an important component of online education, have become increasingly popular in recent years. However, most existing work on student performance prediction targets at online learning platforms with a well-structured curriculum, predefined question order and accurate knowledge tags provided by domain experts. It remains unclear how to conduct student performance prediction in interactive online question pools without such well-organized question orders or knowledge tags by experts. In this paper, we propose a novel approach to boost student performance prediction in interactive online question pools by further considering student interaction features and the similarity between questions. Specifically, we introduce new features (e.g., think time, first attempt, and first drag-and-drop) based on student mouse movement trajectories to delineate students' problem-solving details. In addition, heterogeneous information network is applied to integrating students' historical problem-solving information on similar questions, enhancing student performance predictions on a new question. We evaluate the proposed approach on the dataset from a real-world interactive question pool using four typical machine learning models.Comment: 10 pages, 7 figures, conference lak20, has been accepted, proceeding now. link: https://lak20.solaresearch.org/list-of-accepted-paper

The rise of a connected transnational network

The thesis explores the online practices and the transnational mobilities of a community of Pentecostal Gypsies. The community has diffused from their central hub a Romanian village and is now scattered across Europe. The thesis asks: how does a mobile ethnic group remain united as it transforms from a geographically intensive community to a spatially extensive one? The research design combines analysis of geo-referenced YouTube videos, offline machine code metadata and real world ethnographic data in order to contribute to conceptual debates within migration studies about deterritorialization and the maintenance of social ties after geographical dispersion

Does the Order of Visiting Destinations Affect Their Recall and Evaluation?

Tourists frequently engage in visiting a sequence of cities, sites, and destinations. Previous psychology studies have shown the impact of order on recall and favorability; key concepts are the serial position effect and primacy and recency influences. A field-based natural experiment collected posttrip responses from 179 international tourists to four major Iranian cities. The researchers examined the relationships between the order of visiting the cities, tourists’ recall and judgment. Results from the manipulations revealed there is a relationship (mainly Primacy) between position in the itinerary and their recall. For evaluative judgments, both primacy and recency effects were linked to order of visiting. The work has implications for the presentations of tourism units in a sequence and sharpens the way we use the expression memorable in tourism research