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When the goal of group activities is to support long-term learning, the task of designing well-thought-out collaborative learning (CL) scenarios is an important key to success. To help students adequately acquire and develop their knowledge and skills, a teacher can plan a scenario that increases the probability for learning to occur. Such a scenario defines pedagogically sound structures that prevent off-task behavior and engage students in more meaningful interactions. The main difficulty in designing effective CL scenarios is transforming the teacher's intentions into elements that constitute the learning scenario. This problem is frequently observed when novice teachers attempt to improve the quality of learning and instruction by blending collaborative activities with individual activities without careful planning. With the goal of helping teachers in planning collaborative scenarios, we have developed an intelligent authoring tool referred to as CHOCOLATO using Semantic Web technologies (e.g. ontologies) in order to represent knowledge about different pedagogies and practices related to collaboration. Through the use of this knowledge, CHOCOLATO can provide intelligent guidance that helps teachers to create theory-based CL scenarios which has proven to be effective in a variety of situations. We evaluated it by conducting two experiments. We were interested in verifying whether the recommendations given by CHOCOLATO help novice teachers to design pedagogically sound CL activities, and if these activities help students to learn collaboratively in real classroom settings. The first experiment had the participation of 58 pre-service teachers that created CL scenarios with and without our authoring tool and the second experiment was carried out in a Brazilian public school together with 218 students. The results suggest that the guidance provided by CHOCOLATO do help novice teachers plan, understand and share CL scenarios more easily. They also suggest that the continuous utilization of well-designed theory-based CL activities create favorable conditions for students (particularly less knowledgeable ones) to improve their overall performance throughout the school year. (Contains 11 figures.)

Introduction: There is a global effort to address the school dropout phenomenon. The urgency to act on it comes from the harmful evidence that school dropout has on societal and individual levels. Early Warning Systems (EWS) for school dropout at-risk student identification have been developed to anticipate and help schools have a better chance of acting on it. However, several studies point to a doubt that Correct EWS may come too late because they use only publicly available and general student and school information. We hypothesize that having a tool to assess more subjective and inter-relational factors would help anticipate where and when to act to prevent school dropout. This study aimed to develop a multidimensional measure for assessing relational factors for predicting school dropout (SD) risk in the Brazilian context. Methods: We performed several procedures, including (a) the specialized literature review, (b) the item development of the Relational Factors for the Risk of School Dropout Scale (IAFREE in Portuguese), (c) the content validity analysis, (d) a pilot study, and (e) the administration of the IAFREE to a large Brazilian sample of high school and middle school students (N = 15,924). Results: After the theoretical steps, we found content validity for five relational dimensions for SD (Student-School, Student-School Professionals, Student-Family, Student-Community, and Student-Student) that include 12 facets of risk factors. At the empirical stage, confirmatory analysis corroborated the proposed theoretical model with 12 first-order risk factors and 5 s-order dimensions (36 items). Further, through the Item Response Theory analysis, we assessed the individual item parameters of the items, providing a brief measure without losing psychometric quality (IAFREE-12). Discussion: We discuss how this model may fill gaps in Correct EWS models and how to advance it. The IAFREE is a good measure for scholars investigating the risk of SD. These results are important for implementing an early warning system for SD that looks into the complexity of the school dropout phenomenon. [ABSTRACT FROM AUTHOR]

One of the most useful ways to enhance collaboration is to create scenarios where learners are able to interact more effectively. Nevertheless, the design of pedagogically sound and well-thought-out collaborative learning scenarios is a complex issue. This is due to the context of group learning where the synergy among learners' interactions affects learning processes and, hence, the learning outcome. Although many advances have been made to support the designing of collaborative learning scenarios through technology, a more systematic approach is lacking. With the limitations of the current designing methods and tools, it is difficult to develop intelligent authoring systems that can guide users in order to produce more effective collaboration. One of the main difficulties with creating a more consistent (computer-understandable) approach to designing collaboration is the necessity of proposing better ways to formalize the group learning processes. In this paper, we present an innovative approach that uses ontologies and concepts from learning theories to create a framework that represents collaborative learning and its processes. Ontologies provide the necessary formalization to represent collaboration, while learning theories provide the concepts to justify and support the development of effective learning scenarios. Such an approach contributes to establish the foundations for the development of the next generation of intelligent authoring systems referred to as theory-aware systems. To verify the viability and usefulness of our proposed ontological framework in the context of systematic design, the development and use of an intelligent authoring tool for CSCL design is presented. This system is able to reason on ontologies to give suggestions that help users to create theory-compliant collaborative learning scenarios. We carried out several experiments with teachers in a geometry drawing course and the results indicate that the system helps teachers to create and interchange their scenarios more easily and facilitates the selection of important pedagogical strategies that influence positively the designing and effectiveness of group activities. (Contains 3 tables and 20 figures.)

One of the main difficulties during the design of collaborative learning activities is adequate group formation. In any type of collaboration, group formation plays a critical role in the learners' acceptance of group activities, as well as the success of the collaborative learning process. Nevertheless, to propose both an effective and pedagogically sound group formation is a complex issue due to multiple factors that influence group arrangement. The current (and previous) learner's knowledge and skills, the roles and strategies used by learners to interact among themselves, and the teacher's preferences are some examples of factors to be considered while forming groups. To identify which factors are essential (or desired) in effective group formation, a well-structured and formalized representation of collaborative learning processes, supported by a strong pedagogical basis, is desirable. Thus, the main goal of this paper is to present an ontology that works as a framework based on learning theories that facilitate group formation and collaborative learning design. The ontology provides the necessary formalization to represent collaborative learning and its processes, while learning theories provide support in making pedagogical decisions such as gathering learners in groups and planning the scenario where the collaboration will take place. Although the use of learning theories to support collaborative learning is open for criticism, we identify that they provide important information which can be useful in allowing for more effective learning. To validate the usefulness and effectiveness of this approach, we use this ontology to form and run group activities carried out by four instructors and 20 participants. The experiment was utilized as a proof-of-concept and the results suggest that our ontological framework facilitates the effective design of group activities, and can positively affect the performance of individuals during group learning.

One of the key issues in e-learning environments is the possibility of creating and evaluating exercises. However, the lack of tools supporting the authoring and automatic checking of exercises for specifics topics (e.g., geometry) drastically reduces advantages in the use of e-learning environments on a larger scale, as usually happens in Brazil. This paper describes an algorithm, and a tool based on it, designed for the authoring and automatic checking of geometry exercises. The algorithm dynamically compares the distances between the geometric objects of the student's solution and the template's solution, provided by the author of the exercise. Each solution is a geometric construction which is considered a function receiving geometric objects (input) and returning other geometric objects (output). Thus, for a given problem, if we know one function (construction) that solves the problem, we can compare it to any other function to check whether they are equivalent or not. Two functions are equivalent if, and only if, they have the same output when the same input is applied. If the student's solution is equivalent to the template's solution, then we consider the student's solution as a correct solution. Our software utility provides both authoring and checking tools to work directly on the Internet, together with learning management systems. These tools are implemented using the dynamic geometry software, iGeom, which has been used in a geometry course since 2004 and has a successful track record in the classroom. Empowered with these new features, iGeom simplifies teachers' tasks, solves non-trivial problems in student solutions and helps to increase student motivation by providing feedback in real time. (Contains 10 figures and 6 tables.)

One factor that impacts the quality of Brazilian education is the quality of books and other didactic materials freely distributed throughout the country to public schools, thanks to the Brazilian National Textbook Program. The current evaluation process may take at least two years to complete, involving hundreds of people, and the final result may impact the entire educational system. One of the first activities of the process is to validate and triage the editorial quality attributes of textbooks. However, the validation and triage process needs improvement, considering the gradual expansion of the quantity and variety of materials that currently affect it. This generates risks of reduced quality and timely deliveries. This paper provides a comprehensive critical analysis of the validation and triage process based on the Policy Design Arc framework of Harvard's Kennedy School of Government. We identified causes that affect the quality of deliveries and the time required to conclude tasks. We also propose a theory of change for digital transformation, defining strategies to address the causes of problems, outputs, outcomes, and impacts. Therefore, we have gradually implemented our theory of change in the validation and triage process. [ABSTRACT FROM AUTHOR]

Gamification studies in the educational domain usually focus on motivating students to increase their learning performance by enhancing their motivation. Classifications of behavioural profiles are often used for this (referred to as "gamer" or "user types"), which support the personalization of students' experiences. These classifications consider these profiles from gamers' or non-gamers' points of view. However, within education research, it is necessary to broadly inspect these behavioural profiles to create an instructional design based on learners' intrinsic drivers and motivations. The relationship between these concepts is subjective, complex, and difficult to categorize, demanding research to bridge this gap. Therefore, in this article we present the design and evaluation of an application ontology that seeks to represent relationships between Jung's archetypes (e.g., the Hero, the Outlaw and others) adapted for educational purposes, creating a new approach for modelling user profiles, a taxonomy of game elements specific for use in educational contexts, and Bloom's revised taxonomy to classify learning activities types. This ontology enables personalized and instructional designs directly related to the learning activity type for students. We demonstrate that the proposed ontology can help create better gamification designs to support learning, and we envision it to be used both to create unplugged gamification strategies and personalized gamified educational systems. [ABSTRACT FROM AUTHOR]

The field of Artificial Intelligence (AI) has the potential to improve teaching and learning, for example, by analyzing data produced in educational environments. Furthermore, it can also worsen inequality, as it requires students and instructors to have access to the infrastructure (smartphones or computers) required by the majority of those tools to generate and analyse data. However, access to such infrastructure is not a reality for many students around the world. To shine a light on this problem, this paper investigates, through a Systematic Mapping Study (SMS), initiatives that enable a more inclusive data analysis using AI in education, especially in scenarios with few connectivity resources. We identified that these initiatives are scarce and they are focused in the first phase of the data analysis task: the data collection. Based on the SMS results, we propose a set of recommendations for researchers to offer directions toward a more inclusive analysis of educational data using AI. [ABSTRACT FROM AUTHOR]

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