基于微信公众号的移动学习设计与实践——以泛在学习环境下成人教育类课程为例

近年来,随着智能手机、4G网络、新媒体技术的飞速发展,成教学生学习环境也随之发生了较大的变化,技术的进步让移动学习成为了可能。本文根据移动学习的特点提出了针对性的微型学习策略,以微信公众号为移动学习的载体,创立了融课前分析、学习任务、拓展训练以及学习支持服务为一体的人才培养路径。以移动学习环境分析、学生学情分析、教学内容设计为基础,按接受任务、解决任务、提交成果、考核反馈的流程组织学习活动,通过反思与训练以及线上线下活动进行拓展训练,开展卓有成效的学习支持服务,构建起立体的移动学习模型。     

A systematic review of the role of learning analytics in enhancing feedback practices in higher education

Learning analytics (LA) offers new opportunities to enrich feedback practices in higher education, but little is understood about the ways different LA can enhance feedback practices for educators and students. This systematic literature review maps the current state of implementation of LA to improve feedback practices in technology-mediated learning environments in higher education. We used strict inclusion criteria to select relevant studies that have investigated the role of LA on feedback practices. To identify common features of LA for feedback studies, we coded relevant publications using an analytical framework that identifies four key dimensions of LA systems: what (types of data), how (analytic methods), why (objectives), and how educators and students are served by LA (stakeholders). Based on findings, we propose a conceptual framework that can guide the implementation of LA for feedback systems and also suggest future empirical research in this area.     

全景透视多模态学习分析的数据整合方法

多模态学习分析被认为是学习分析研究的新生长点,其中,多模态数据如何整合是推进学习分析研究的难点。利用系统文献综述及元分析方法,有助于为研究和实践领域提供全景式的关于多模态数据整合的方法与策略指导。通过对国内外363篇相关文献的系统分析发现:(1)多模态学习分析中的数据类型主要包含数字空间数据、物理空间数据、生理体征数据、心理测量数据和环境场景数据等5类。在技术支持的教与学环境中,高频、精细、微观的多模态学习数据变得可得、易得、准确。(2)多模态学习分析中的学习指标主要有行为、注意、认知、元认知、情感、协作、交互、投入、学习绩效和技能等。随着技术的发展和人们对学习过程的深刻洞察,学习指标也会变得更加精细化。(3)数据与指标之间展现出"一对一""一对多"和"多对一"三种对应关系。把握数据与指标之间的复杂关系是数据整合的前提,测量学习指标时既要考虑最适合的数据,也要考虑其他模态数据的补充。(4)多模态学习分析中的数据整合方式主要有"多对一""多对多"和"三角互证"三种,旨在提高测量的准确性、信息的全面性和整合的科学性。总之,多模态数据整合具有数据的多模态、指标的多维度和方法的多样性等三维特性。将多模态数据时间线对齐是实现数据整合的关键环节,综合考虑三维特性提高分析结果的准确性是多模态数据整合未来研究的方向。     

Using learning analytics in the Amazonas: understanding students’ behaviour in introductory programming

Tools for automatic grading programming assignments, also known as Online Judges, have been widely used to support computer science (CS) courses. Nevertheless, few studies have used these tools to acquire and analyse interaction data to better understand the students’ performance and behaviours, often due to data availability or inadequate granularity. To address this problem, we propose an Online Judge called CodeBench, which allows for fine-grained data collection of student interactions, at the level of, eg, keystrokes, number of submissions, and grades. We deployed CodeBench for 3 years (2016–18) and collected data from 2058 students from 16 introductory computer science (CS1) courses, on which we have carried out fine-grained learning analytics, towards early detection of effective/ineffective behaviours regarding learning CS concepts. Results extract clear behavioural classes of CS1 students, significantly differentiated both semantically and statistically, enabling us to better explain how student behaviours during programming have influenced learning outcomes. Finally, we also identify behaviours that can guide novice students to improve their learning performance, which can be used for interventions. We believe this work is a step forward towards enhancing Online Judges and helping teachers and students improve their CS1 teaching/learning practices.     

Coordinating learning analytics policymaking and implementation at scale

Many Latin-American institutions recognise the potential of learning analytics (LA). However, the number of actual LA implementations at scale remains limited, notwithstanding considerable effort made to formulate guidelines and frameworks to support the LA policy development. Guidance on how to coordinate the interaction between the LA policymaking and implementation is mostly missing, leaving a difficult challenge up to practitioners. In this study we propose a coordination model to support future LA initiatives at scale. We explore the problem by comparing two cases in Belgium and Ecuador. Following up we use the LA implementation timeline as a driver for planning the interaction between the policymaking and implementation. We continue by testing an application of the model with LA experts predominantly from Latin-American institutions, asking them to map low-level items of the SHEILA policy framework to four implementation phases. The results of this mapping support that LA policy building can be spread over time, that it can coincide with LA implementation at scale, and that both efforts can be coordinated. It is hoped that this study will provide additional guidance for future Latin-American and other LA initiatives.     

Validity evidence for the Experiences of Teaching and Learning Questionnaire (ETLQ) in evaluations of quality learning: A systematic critical literature review

The use of the Experiences of Teaching & Learning Questionnaire (ETLQ) for the evaluation of learning quality in higher education has been expanding during the last decade, thus a review of the instrument’s validity evidence is warranted. The design of the study was a systematic critical literature review. We evaluated the strength of the validity evidence of 17 included studies with a quality appraisal framework reflecting current standards for educational testing. The evidence supporting the central validity assumptions of the ETLQ scales is currently weak to moderate and incomplete. Thus, caution against the uncritical use of ETQL scores for high-stakes educational decisions is warranted. The appraisal framework used was useful for creating an overview of the evidence. However, attention to more general aspects of study quality, and consensus deliberations with three to four raters was also important for sufficiently reliable appraisal of the evidence.     

Learning analytics initiatives in Latin America: Implications for educational researchers,practitioners and decision makers

This study presents several Latin American research initiatives in the field of learning analytics (LA). The study’s purpose is to enhance awareness and understanding of LA among researchers, practitioners and decision makers, and to highlight the importance of supporting research on LA. We analyzed case studies of LA research conducted at four levels of the educational system (the national, institutional, classroom and student levels), which were implemented in four countries (Brazil, Ecuador, Mexico and Uruguay). Diversified cases were selected to demonstrate the use of LA in primary, secondary and higher education, and to allow the inclusion of different types of datasets. These cases also showed the development of legal frameworks for handling ethical issues, and they met the requirements for data privacy protection in Latin America. The study concludes with a discussion of the findings and their implications for further research and practice in the field of LA for teaching and learning.     

Expanding horizons for students with dyslexia in the 21st century: universal design and mobile technology

This paper discusses the role of mobile technology in supporting people with dyslexia within the theoretical framework of Universal Design for Learning. The authors discuss how students with dyslexia can use mobile technology to address a diverse range of academic needs (such as reading, composing text, notetaking, metacognition and studying skills). Curriculum issues and teacher training are also examined.     

Adaptation and evaluation of a learning analytics dashboard to improve academic support at three Latin American universities

Despite the success of academic advising dashboards in several higher educational institutions (HEI), these dashboards are still under-explored in Latin American HEI's. To close this gap, three different Latin American universities adapted an existing advising dashboard, originally deployed at the KU Leuven to their own context. In all three cases, the context was the main ruling factor to these adaptations. In this paper, we describe these adaptions using a framework that focuses on four different elements of the context: Objectives, Stakeholders, Key moment and Interactions. Evaluation of the adapted dashboards in the three different Latin American universities is conducted through pilots. This evaluation shows the value of the dashboard approach in different contexts in terms of satisfaction, usefulness and impact in academic decision-making and advising tasks. The main contribution of this paper is the systematic reporting of the adaptations to an academic advising dashboard and showing the value of an academic advising dashboard on academic decision-making and advising tasks.     

Towards convergence of mobile and psychological theories of learning

This special issue was designed to promote an integration of mobile and psychological theories of learning by inviting empirical research that draws upon both theoretical approaches to guide investigation into learning involving mobile devices. Five empirical articles illustrated how mobile devices afford resources to learners and how new channels of data afford researchers new insight into learning processes. Authors of two invited commentaries note the challenges involved in researching mobile learning, which unfolds across multiple contexts and can involve novel tools, multiple learners, and instructors and experts. These authors propose a taxonomy that can organize research that investigates interactions amongst learners, instructors, experts, and tools across one or more physical contexts, as well as a research agenda that would empirically test and refine assumptions made by mobile learning theorists. In this commentary, the editorial team proposes that mobile and psychological theories may be improved through convergence. Theories of mobile learning can be advanced by adopting practices previously employed to refine psychological theories of learning, whereas conducting research using mobile devices (and the data they provide) can further refine psychological theories of learning. We illustrate these positions with examples, and consider how instruction must be designed and how learners must be prepared in order to benefit from learning using mobile technology.     

Learning analytics: challenges and limitations

Learning analytic implementations are increasingly being included in learning management systems in higher education. We lay out some concerns with the way learning analytics – both data and algorithms – are often presented within an unproblematized Big Data discourse. We describe some potential problems with the often implicit assumptions about learning and learners – and indeed the tendency not to theorize learning explicitly – that underpin such implementations. Finally, we describe an attempt to devise our own analytics, grounded in a sociomaterial conception of learning. We use the data obtained to suggest that the relationships between learning and the digital traces left by participants in online learning are far from trivial, and that any analytics that relies on these as proxies for learning tends towards a behaviorist evaluation of learning processes.     

Models of Self-regulated Learning: A review

Questions connected with the regulation of one's own cognitive processes attract increasing numbers of researchers in psychology, as evidenced by the several different models of self-regulation that have been developed over the past two decades. The aim of this article was to present and compare the latest models of self-regulated learning (SRL), including those by Boekaerts, Borkowski, Pintrich, Winne and Zimmerman. The models were compared on four criteria (i.e. background theories, definitions of SRL, components included in the models and empirical work). The results show that theoretical background is an important differentiating feature. The two models that resembled each other more than any other two models (i.e. Pintrich and Zimmerman) were inspired by the same background theory (i.e. social cognitive theory). On the other hand, the models that differed most from the other models (i.e. Borkowski and Winne) were also theoretically the farthest removed ones.     

微信移动学习的支持功能与设计原则分析

微信是一款具有通讯、社交、平台化功能的移动性应用软件。在大学生群体中使用广泛,构建了移动互联网环境下一种新型的学习支持环境。在已有文献梳理的基础上,研究了微信的移动学习支持功能,从语音文本交互、微信群、自动回复响应、订阅推送和内容分享等角度进行了分析;对微信、QQ、微博主要社会媒体的学习支持特征进行了比较,并分析了微信与学习者个人学习环境要素间的协同关系。在移动学习通用设计准则的指导下．从定位、功能、内容、交互、学习方式、网络服务的层面,探讨了微信移动学习的设计原则。最后,从不同情境下讨论了微信移动学习的具体应用案例。通过对微信移动学习支持功能与设计原则的探索．旨在对本领域的研究与实践提供理论上的借鉴和参考。     

A systematic review of teacher guidance during collaborative learning in primary and secondary education

For this review, we synthesized quantitative and qualitative research on collaborative learning to examine the relationship between teacher guidance strategies and the processes and outcomes of collaboration among students (66 studies). The results show that several aspects of teacher guidance are positively related to student collaboration, for example when teachers focus their attention on students’ problem solving strategies. During student collaboration, opportunities arise for students to engage in collaborative activities that support their learning process. The way teachers take more or less control of these moments determines whether these opportunities can be turned into real moments of learning for the students. This review highlights the important yet challenging role of the teacher during collaborative learning.     

Facilitating flexible learning by replacing classroom time with an online learning environment: A systematic review of blended learning in higher education

Higher education institutions are trying to provide more flexibility and individualization, which is mainly realized through the use of new technologies and implemented in online or blended learning designs. This systematic review aims to investigate the impact of replacing classroom time with an online learning environment. The meta-analysis (k = 21 effect sizes) applied strict inclusion criteria concerning research design, measurement of learning outcomes and implementation of blended learning. The estimated effect size (Hedge's g) was positive, although not significantly different from zero and the confidence interval [-0.13, 0.25], suggesting that overall differences between blended and conventional classroom learning are small, and, at best, very small negative or moderate positive effects are plausible. This means that despite a reduction in classroom time between 30 and 79 per cent, equivalent learning outcomes were found. Consequently, blended learning with reduced classroom time is not systematically more or less effective than conventional classroom learning.     

不同学习阶段学习策略研究述评

学习策略的相关研究已成为教育学、心理学等研究领域的关注点之一,对当前国内外学习策略研究的基本脉络、不同条件和阶段下学习策略相关研究进展作出总结和归纳,以期为国内学习策略的深入研究提供借鉴。     

Experiences from employees with team learning in a vocational learning or work setting: A systematic review of qualitative evidence

This qualitative evidence synthesis aimed to integrate findings on the experiences of employees with team learning in the context of their work or vocational learning setting. The meta-aggregative approach to qualitative evidence synthesis was used to summarize the findings from original research papers in which the experiential level of employees was investigated. The findings suggest that employees learn for different reasons and in different ways. Three major lines of actions for practice and policy were developed from the synthesis. A first advice is to stimulate communication, boundary crossing and knowledge sharing and establish an enabling learning environment that triggers positive factors for team learning. Secondly, it is important to analyse the authority structures that influence the relationships within a team, minimise the power inequalities that flow from hierarchical differences, and support and enable team leaders to influence the power differences inside their team. Finally, it is recommended to try to recognise the authenticity, the commitment and devotion of employees toward team learning, to stimulate but not to intervene in the natural process of team learning, and to consider the place of reflection and action in this process.     

Towards learning analytics adoption: A mixed methods study of data-related practices and policies in Latin American universities

In Latin American universities, Learning Analytics (LA) has been perceived as a promising opportunity to leverage data to meet the needs of a diverse student cohort. Although universities have been collecting educational data for years, the adoption of LA in this region is still limited due to the lack of expertise and policies for processing and using educational data. In order to get a better picture of how existing data-related practices and policies might affect the incorporation of LA in Latin American institutions, we conducted a mixed methods study in four Latin American universities (two Chilean and two Ecuadorian). In this paper, the qualitative data were based on 37 interviews with managers and 16 focus groups with 51 teaching staff and 45 students; the quantitative data were collected through two surveys answered by 1884 students and 368 teachers, respectively. The findings reveal opportunities to incorporate LA services into existing data practices in the four case studies. However, the lack of reliable information systems and policies to regulate the use of data imposes challenges that need to be overcome for future LA adoption.