Assessment of 21st century ICT skills in Chile: Test design and results from high school level students

This paper describes a study that evaluates fifteen-year-old Chilean students Information and Communication Technology (ICT) skills. The paper presents an operational definition of ICT skills, an instrument measuring these skills as well as the students' results in the test. The definition of ICT skills used considers Chile's curricular framework, functional and cognitive skills. Specifically, ICT skills were defined as the capacity to solve problems of information, communication and knowledge in digital environments. A performance-based assessment was designed in a virtual environment to measure these skills. The analysis of the results showed that the majority of students were able to solve tasks related to the use of information as consumers, i.e., approximately three quarters of the students were able to search for information and half of them were also able to organize and manage digital information. Additionally, they show that very few students were able to succeed in tasks related to the use of information as producers, i.e., only one third of the students were able to develop their own ideas in a digital environment and less than one fifth were able to refine digital information and create a representation in a digital environment. Socioeconomic group, access, daily use and confidence in doing ICT-related activities were all positively associated with higher scores, showing the need to implement strategies to compensate this inequality, possibly by explicitly defining these aims in the national curriculum.     

Augmented reality and competition in robotics education: Effects on 21st century competencies,group collaboration and learning motivation

Robotics education has received an increasing attention in recent years as a means to build students' motivation, team collaboration skills, and other valuable 21st century competencies. Yet there is a lack of experimental studies to investigate and identify strategies to facilitate robotics education. This study adopted a 2 × 2 quasi-experimental design to investigate two strategies: the incorporation of augmented reality (AR) and the introduction of competition in robotics activities. Students' robotics task performance, team collaboration processes, 21st century learning competencies and learning motivation were measured as dependent variables. The results indicated that AR significantly improved students' motivation, team processes, and 21st century competencies. Moreover, the effects of AR were more pronounced with the competition groups. Implications are drawn to provide guidelines on the use of AR and competition in robotics education.     

Digital game-based learning in a Shanghai primary-school mathematics class: A case study

This study examined the perceptions and experiences of a teacher and students in a Shanghai public primary school when digital games were used in a second-grade math class. The participants included one teacher and 45 students. Data collection methods included classroom observation, focus-group and individual interviews, and document analysis. Digital gameplay, when used once daily over a 6-day period, was found to enhance student engagement and interest in learning; many students, however, were concerned about its effect on academic achievement and eyesight. The teacher employed a “making thinking visible” approach using pencil and paper and problem-solving strategies to help students understand the game's mathematical principles and master mathematical knowledge. Obstacles included large class size, difficulty evaluating learning outcomes, balancing fun and learning, and effective game–classroom integration. This study found that exam-oriented education and traditional teacher-centred teaching in China influenced participants' perceptions and experiences of digital game-based learning.     

An implementation of design-based learning through creating educational computer games: A case study on mathematics learning during design and computing

This mixed-method case study examined the potential of computer-assisted, math game making activities in facilitating design-based math learning for school children. Sixty-four middle school children participated in Scratch-based, math game making activities. Data were collected via activity and conversation observation, artifact analysis, interviewing, and survey. The study findings indicated that participants developed significantly more positive dispositions toward mathematics after computer game making. The study also found that experience-driven game design processes helped to activate children's reflection on everyday mathematical experiences. Mathematical thinking and content experience were intertwined within the process of computer game authoring. On the other hand, children designers were involved in game-world and story crafting more than mathematical representation. And it was still challenging for them to perform computer game coding with abstract reasoning.     

Data Mining and Information Retrieval in the 21st century: A bibliographic review

Data Mining and Information Retrieval is an emerging interdisciplinary discipline dealing with Information Retrieval and Data Mining techniques. It has undergone rapid development with the advances in mathematics, statistics, information science, and computer science. In this paper, we present an empirical analysis of publication metadata obtained from 6 top-tier journals and 9 conferences for the first 16 years of the 21st Century, and evaluate the dynamic characteristics of Data Mining and Information Retrieval. We find a steady growth both in terms of productivity and impact, evidenced by the unabated number of publications/citations over the period of study. We note that the modality for co-operation in this field is changing from independent to collaborative. Furthermore, according to the citation pattern, the field is becoming open-minded as illustrated by a gradual decline of self-citation rates, which was dropped to 10% in 2015, nearly three times lower than what it was in 2000. Finally, we explore the inner structure relying on the topics evolution from the aspects of popular keywords/topics identification and evolution. Overall, this study provides insights of Data Mining and Information Retrieval behind its demonstrated growth in the recent past, with the ultimate goal of revealing its potential of driving scientific innovation in the future.     

多智能体博弈、学习与控制

近年来, 人工智能(Artificial intelligence, AI)技术在棋牌游戏、计算机视觉、自然语言处理和蛋白质结构解析与预测等研究领域取得了众多突破性进展, 传统学科之间的固有壁垒正在被逐步打破, 多学科深度交叉融合的态势变得越发明显. 作为现代智能科学的三个重要组成部分, 博弈论、多智能体学习与控制论自诞生之初就逐渐展现出一种“你中有我, 我中有你” 的关联关系. 特别地, 近年来在AI技术的促进作用下, 这三者间的交叉研究成果正呈现出一种井喷式增长的态势. 为及时反映这一学术动态和趋势, 本文对这三者的异同、联系以及最新的研究进展进行了系统梳理. 首先, 介绍了作为纽带连接这三者的四种基本博弈形式, 进而论述了对应于这四种基本博弈形式的多智能体学习方法; 然后, 按照不同的专题, 梳理了这三者交叉研究的最新进展; 最后, 对这一新兴交叉研究领域进行了总结与展望.     

Teacher perceptions of using mobile phones in the classroom: Age matters!

This study examined the digital native–digital immigrant dichotomy based on the results of a study involving 1095 teachers from two states in the southeastern United States. The study focused on age as it relates to the relationship between the type of mobile phone they owned, their support for the use of mobile phones in the classroom, their perceptions of the benefits of specific mobile features for school-related work, and their perceptions of instructional barriers. The results indicated that the age of the teacher matters, however, not as suggested by Prensky (2001). There were no significant differences in the findings for the teachers who were less than 32 and the ones who were 33–49; however, they both significantly differed from those over 50 in mobile phone ownership and support for the use of mobile phones in the classroom as well as in their perceptions regarding the useful mobile features for school-related work and instructional barriers. In each instance, the older teachers were less likely to own smartphones, were less supportive on all items, were less enthusiastic about the features, and found the barriers to be more problematic.     

Learning curve models and applications: Literature review and research directions

Learning curves (LCs) are deemed effective tools for monitoring the performance of workers exposed to a new task. LCs provide a mathematical representation of the learning process that takes place as task repetition occurs. These curves were originally proposed by Wright in 1936 upon observing cost reduction due to repetitive procedures in production plants. Since then, LCs have been used to estimate the time required to complete production runs and the reduction in production costs as learning takes place, as well as to assign workers to tasks based on their performance profile. Further, effects of task interruption on workers’ performance have also being modeled by modifications on the LCs. This wide variety of applications justifies the relevance of LCs in industrial applications. This paper presents the state of the art in the literature on learning and forgetting curves, describing the existing models, their limitations, and reported applications. Directions for future research on the subject are eventually proposed.

Relevance to industry

The Learning Curve (LC) models described here can be used in a wide variety of industrial applications where workers endeavor new tasks. LC modeling enables better assignment of tasks to workers and more efficient production planning, and reduces production costs.     

AWESOME: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents

Two minimal requirements for a satisfactory multiagent learning algorithm are that it 1. learns to play optimally against stationary opponents and 2. converges to a Nash equilibrium in self-play. The previous algorithm that has come closest, WoLF-IGA, has been proven to have these two properties in 2-player 2-action (repeated) games—assuming that the opponent’s mixed strategy is observable. Another algorithm, ReDVaLeR (which was introduced after the algorithm described in this paper), achieves the two properties in games with arbitrary numbers of actions and players, but still requires that the opponents' mixed strategies are observable. In this paper we present AWESOME, the first algorithm that is guaranteed to have the two properties in games with arbitrary numbers of actions and players. It is still the only algorithm that does so while only relying on observing the other players' actual actions (not their mixed strategies). It also learns to play optimally against opponents that eventually become stationary. The basic idea behind AWESOME (Adapt When Everybody is Stationary, Otherwise Move to Equilibrium) is to try to adapt to the others' strategies when they appear stationary, but otherwise to retreat to a precomputed equilibrium strategy. We provide experimental results that suggest that AWESOME converges fast in practice. The techniques used to prove the properties of AWESOME are fundamentally different from those used for previous algorithms, and may help in analyzing future multiagent learning algorithms as well. Editors: Amy Greenwald and Michael Littman     

Superiority of collaborative learning with complex tasks: A research note on an alternative affective explanation

Kirschner, Paas, and Kirschner (2009c) used the theoretical framework of cognitive load to explain why the learning of a group of collaborating individuals was more efficient than that of individuals learning alone with high-complexity tasks but not with low-complexity tasks. The authors argued that collaboration circumvented the limitations of an individual’s working memory by creating an expanded cognitive capacity and by allowing for the distribution of cognitive load among group members. Inspired by research on efficacy, this study explored an alternative affective explanation of the results. By measuring the amount of mental effort learners expected to invest in working on a learning task before actually carrying out the task, this study showed that learners who had to collaboratively solve a high-complexity problem expected to invest less mental effort than learners who had to solve the problem alone. When confronted with low-complexity tasks, the expected amount of mental effort did not differ.     

Creativity,method and process in digital fabric printing: a 21st century paintbrush

Abstract

This paper analyses how the arrival and widespread use of digital printing affects the artist as maker in the postmodern world of instant reproduction. In response to the question of using digital printing as an artistic tool, a 21^st century paintbrush, the marks and imagery of paintings and drawings of the author's own work produced over the past few years were analysed. The digitally printed fabric outcomes, large scale painterly prints, will be presented as examples of how digitisation becomes a powerfultoolto the textile artist with the creative textile maker manipulating technology and not being controlled by it. The conclusion will show how digitisation and new technologies should not be seen as creating isolation but can be integrated into the textile artist's tool box to inspire and enhance creativity.     

A dialogic understanding of the relationship between CSCL and teaching thinking skills

How to teach flexible thinking and learning skills, particularly creativity and the skill of “learning to learn,” is a key concern for CSCL in the context of the emerging Networked Society. The currently dominant paradigms for supporting pedagogical design within CSCL, including socio-cultural theory, are limited in the support that they can offer to the project of teaching general thinking skills. This paper uses critical literature review, conceptual analysis, and evidence from case studies to argue for the value of a dialogic interpretative framework that links the goal of teaching thinking with the method of CSCL. The evidence reviewed suggests that dialogue is itself the primary thinking skill from which all others are derived. It is argued from this that dialogic theory offers a possible solution to the problem of how to conceptualize general thinking skills for CSCL: this is that teaching dialogue as an end in itself promotes the learning of general thinking skills. Implications of the proposed framework for pedagogical design are brought out through case studies illustrating the use of CSCL to broaden and deepen dialogic spaces of reflection.     

Non-IID data and Continual Learning processes in Federated Learning: A long road ahead

Federated Learning is a novel framework that allows multiple devices or institutions to train a machine learning model collaboratively while preserving their data private. This decentralized approach is prone to suffer the consequences of data statistical heterogeneity, both across the different entities and over time, which may lead to a lack of convergence. To avoid such issues, different methods have been proposed in the past few years. However, data may be heterogeneous in lots of different ways, and current proposals do not always determine the kind of heterogeneity they are considering. In this work, we formally classify data statistical heterogeneity and review the most remarkable learning Federated Learning strategies that are able to face it. At the same time, we introduce approaches from other machine learning frameworks. In particular, Continual Learning strategies are worthy of special attention, since they are able to handle habitual kinds of data heterogeneity. Throughout this paper, we present many methods that could be easily adapted to the Federated Learning settings to improve its performance. Apart from theoretically discussing the negative impact of data heterogeneity, we examine it and show some empirical results using different types of non-IID data.     

Master in Teacher Training: A real implementation of Active Learning

Teaching methods based on lectures often result in student passivity rather than pro-activity with the only goal of the student being to pass the final exam. Consequently, content retention is temporary and true learning is not achieved. Lack of student motivation can be solved by using Active Learning methodologies: serious games, Project-Based Learning (PBL), blended learning, etc. In addition, these methodologies enhance the development of the competences of students and provide a better evaluation of outcomes, provided adequate tools are used. However, apart from this, a more profound use of Information and Communications Technology (ICT) is needed to improve the effectiveness of learning and to create a learning system adapted to our current society. Learning Management Systems (LMS), social networks and blogs are indispensable for the efficient application of innovative learning methodologies. The Master in Teacher Training (MTT) provides an ideal case study as the most relevant features of Active Learning are present. The main contributions to this learning environment have been the incorporation of Active Learning methodologies (using real scenarios and project-based collaborative learning), an innovative method for assessing the Master and the impact of technology in learning. All of these have resulted in very positive results in relative to academic marks, surveys and entrepreneurship.     

Interactive Videoconferencing for collaborative learning at a distance in the school of 21st century: A case study in elementary schools in Greece

The aim of this paper is to present the design, implementation and evaluation of the methodology which focuses on the pedagogical utilization of Interactive Videoconferencing (IVC) in the contemporary elementary school.     

Plausible Justification Trees: A Framework for Deep and Dynamic Integration of Learning Strategies

This article describes a framework for the deep and dynamic integration of learning strategies. The framework is based on the idea that each single-strategy learning method is ultimately the result of certain elementary inferences (like deduction, analogy, abduction, generalization, specialization, abstraction, concretion, etc.). Consequently, instead of integrating learning strategies at a macro level, we propose to integrate the different inference types that generate individual learning strategies. The article presents a concept-learning and theory-revision method that was developed in this framework. It allows the system to learn from one or from several (positive and/or negative) examples, and to both generalize and specialize its knowledge base. The method integrates deeply and dynamically different learning strategies, depending on the relationship between the input information and the knowledge base. It also behaves as a single-strategy learning method whenever the applicability conditions of such a method are satisfied.     

The impact of learning design on student behaviour,satisfaction and performance: A cross-institutional comparison across 151 modules

Pedagogically informed designs of learning are increasingly of interest to researchers in blended and online learning, as learning design is shown to have an impact on student behaviour and outcomes. Although learning design is widely studied, often these studies are individual courses or programmes and few empirical studies have connected learning designs of a substantial number of courses with learning behaviour. In this study we linked 151 modules and 111.256 students with students' behaviour (<400 million minutes of online behaviour), satisfaction and performance at the Open University UK using multiple regression models. Our findings strongly indicate the importance of learning design in predicting and understanding Virtual Learning Environment behaviour and performance of students in blended and online environments. In line with proponents of social learning theories, our primary predictor for academic retention was the time learners spent on communication activities, controlling for various institutional and disciplinary factors. Where possible, appropriate and well designed communication tasks that align with the learning objectives of the course may be a way forward to enhance academic retention.