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1.
Game-based learning environments hold significant promise for facilitating learning experiences that are both effective and engaging. To support individualised learning and support proactive scaffolding when students are struggling, game-based learning environments should be able to accurately predict student knowledge at early points in students' gameplay. Student knowledge is traditionally assessed prior to and after each student interacts with the learning environment with conventional methods, such as multiple choice content knowledge assessments. While previous student modelling approaches have leveraged machine learning to automatically infer students' knowledge, there is limited work that incorporates the fine-grained content from each question in these types of tests into student models that predict student performance at early junctures in gameplay episodes. This work investigates a predictive student modelling approach that leverages the natural language text of the post-gameplay content knowledge questions and the text of the possible answer choices for early prediction of fine-grained individual student performance in game-based learning environments. With data from a study involving 66 undergraduate students from a large public university interacting with a game-based learning environment for microbiology, Crystal Island , we investigate the accuracy and early prediction capacity of student models that use a combination of gameplay features extracted from student log files as well as distributed representations of post-test content assessment questions. The results demonstrate that by incorporating knowledge about assessment questions, early prediction models are able to outperform competing baselines that only use student game trace data with no question-related information. Furthermore, this approach achieves high generalisation, including predicting the performance of students on unseen questions.

Practitioner notes

What is already known about this topic
  • A distinctive characteristic of game-based learning environments is their capacity to enable fine-grained student assessment.
  • Adaptive game-based learning environments offer individualisation based on specific student needs and should be able to assess student competencies using early prediction models of those competencies.
  • Word embedding approaches from the field of natural language processing show great promise in the ability to encode semantic information that can be leveraged by predictive student models.
What this paper adds
  • Investigates word embeddings of assessment question content for reliable early prediction of student performance.
  • Demonstrates the efficacy of distributed word embeddings of assessment questions when used by early prediction models compared to models that use either no assessment information or discrete representations of the questions.
  • Demonstrates the efficacy and generalisability of word embeddings of assessment questions for predicting the performance of both new students on existing questions and existing students on new questions.
Implications for practice and/or policy
  • Word embeddings of assessment questions can enhance early prediction models of student knowledge, which can drive adaptive feedback to students who interact with game-based learning environments.
  • Practitioners should determine if new assessment questions will be developed for their game-based learning environment, and if so, consider using our student modelling framework that incorporates early prediction models pretrained with existing student responses to previous assessment questions and is generalisable to the new assessment questions by leveraging distributed word embedding techniques.
  • Researchers should consider the most appropriate way to encode the assessment questions in ways that early prediction models are able to infer relationships between the questions and gameplay behaviour to make accurate predictions of student competencies.
  相似文献   

2.
Collaborative inquiry learning affords educators a context within which to support understanding of scientific practices, disciplinary core ideas, and crosscutting concepts. One approach to supporting collaborative science inquiry is through problem-based learning (PBL). However, there are two key challenges in scaffolding collaborative inquiry learning in technology rich environments. First, it is unclear how we might understand the impact of scaffolds that address multiple functions (e.g., to support inquiry and argumentation). Second, scaffolds take different forms, further complicating how to coordinate the forms and functions of scaffolds to support effective collaborative inquiry. To address these issues, we identify two functions that needed to be scaffolded, the PBL inquiry cycle and accountable talk. We then designed predefined hard scaffolds and just-in-time soft scaffolds that target the regulation of collaborative inquiry processes and accountable talk. Drawing on a mixed method approach, we examine how middle school students from a rural school engaged with Crystal Island: EcoJourneys for two weeks (N=45). Findings indicate that hard scaffolds targeting the PBL inquiry process and soft scaffolds that targeted accountable talk fostered engagement in these processes. Although the one-to-one mapping between form and function generated positive results, additional soft scaffolds were also needed for effective engagement in collaborative inquiry and that these soft scaffolds were often contingent on hard scaffolds. Our findings have implications for how we might design the form of scaffolds across multiple functions in game-based learning environments.  相似文献   

3.
ABSTRACT

Digital games are very popular in modern culture. The authors are examining ways to leverage these engaging environments to assess and support student competencies. The authors examine gameplay and learning using a physics game they developed called Newton's Playground. The sample consisted of 167 eighth- and ninth-grade students who played Newton's Playground for about 4 hr over the course of 1.5 weeks. Findings include significant pretest–posttest physics gains, and significant relations between in-game indicators and learning.  相似文献   

4.
学习分析自从2011年出现以来,不管是作为一个研究重点还是实践领域,它一直在发展,从某种程度上讲已经成熟了。学习分析不但在增进我们对学生坚持学习和顺利完成学业的了解以及提高我们教学策略的效果等方面有巨大潜能,它还能帮助学生在更加知情的情况下做出选择。然而,学习分析在多大程度上影响学生学习?它在什么条件下能够充分发挥其潜能?这些问题引起一些关注。我们在这篇概念性文章中提出从生态系统观的角度理解学习分析,或是把它视为某一个生态系统的一部分,或是把它当成一个生态系统,这个系统由各种人为和非人为因素(行动者)组成,包含一系列相互交叉、常常互相依存且又是彼此一部分的变量。鉴于学习分析有提高学习效果的潜能,我们基于学习的社会批判视角提出学习分析的生态系统观。我们从机构和机构以外社会层面的微观、中观和宏观因素出发对学习分析进行阐述。学习分析的生态系统观不认为学生对自己的学习可以免责,而是更加细致入微地了解促成(或妨碍)学习发生的因素(行动者)。  相似文献   

5.
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6.
ABSTRACT

Traditional lecture theatre environments present significant challenges in higher education, in light of increasingly large and diverse student populations. This small-scale study explores how blended learning through the game-based platform Kahoot! can be used to enhance the learning experience offered to students in these spaces, from the perspective of 44 final-year primary education undergraduates. An action research approach was employed with data collected from pre- and post-lecture surveys. Findings suggest that the integration of synchronous online learning in lecture theatres presented no technical difficulties and that gaming was successful in enabling active participation and interactive learning. Students valued its competitive nature, the immediacy of feedback on their knowledge and structured opportunities for further discussion. Students reported improvements in engagement, concentration and retention, although results for the latter were more ambiguous and would benefit from further investigation.  相似文献   

7.
This article reports on a trace-based assessment of approaches to learning used by middle school aged children who interacted with NASA Mars Mission science, technology, engineering and mathematics (STEM) games in Whyville, an online game environment with 8 million registered young learners. The learning objectives of two games included awareness and knowledge of NASA missions, developing knowledge and skills of measurement and scaling, applying measurement for planetary comparisons in the solar system. Trace data from 1361 interactions were analysed with nonparametric multidimensional scaling methods, which permitted visual examination and statistical validation, and provided an example and proof of concept for the multidimensional scaling approach to analysis of time-based behavioural data from a game or simulation. Differences in approach to learning were found illustrating the potential value of the methodology to curriculum and game-based learning designers as well as other creators of online STEM content for pre-college youth. The theoretical framework of the method and analysis makes use of the Epistemic Network Analysis toolkit as a post hoc data exploration platform, and the discussion centres on issues of semantic interpretation of interaction end-states and the application of evidence centred design in post hoc analysis.

Practitioner notes

What is already known about this topic
  • Educational game play has been demonstrated to positively affect learning performance and learning persistence.
  • Trace-based assessment from digital learning environments can focus on learning outcomes and processes drawn from user behaviour and contextual data.
  • Existing approaches used in learning analytics do not (fully) meet criteria commonly used in psychometrics or for different forms of validity in assessment, even though some consider learning analytics a form of assessment in the broadest sense.
  • Frameworks of knowledge representation in trace-based research often include concepts from cognitive psychology, education and cognitive science.
What this paper adds
  • To assess skills-in-action, stronger connections of learning analytics with educational measurement can include parametric and nonparametric statistics integrated with theory-driven modelling and semantic network analysis approaches widening the basis for inferences, validity, meaning and understanding from digital traces.
  • An expanded methodological foundation is offered for analysis in which nonparametric multidimensional scaling, multimodal analysis, epistemic network analysis and evidence-centred design are combined.
Implications for practice and policy
  • The new foundations are suggested as a principled, theory-driven, embedded data collection and analysis framework that provides structure for reverse engineering of semantics as well as pre-planning frameworks that support creative freedom in the processes of creation of digital learning environments.
  相似文献   

8.
This study examined how scaffolds and student achievement levels influence inquiry and performance in a problem-based learning environment. The scaffolds were embedded within a hypermedia program that placed students at the center of a problem in which they were trying to become the youngest person to fly around the world in a balloon. One-hundred and eleven seventh grade students enrolled in a science and technology course worked in collaborative groups for a duration of 3 weeks to complete a project that included designing a balloon and a travel plan. Student groups used one of three problem-based, hypermedia programs: (1) a no scaffolding condition that did not provide access to scaffolds, (2) a scaffolding optional condition that provided access to scaffolds, but gave students the choice of whether or not to use them, and (3) a scaffolding required condition required students to complete all available scaffolds. Results revealed that students in the scaffolding optional and scaffolding required conditions performed significantly better than students in the no scaffolding condition on one of the two components of the group project. Results also showed that student achievement levels were significantly related to individual posttest scores; higher-achieving students scored better on the posttest than lower-achieving students. In addition, analyses of group notebooks confirmed qualitative differences between students in the various conditions. Specifically, those in the scaffolding required condition produced more highly organized project notebooks containing a higher percentage of entries directly relevant to the problem. These findings suggest that scaffolds may enhance inquiry and performance, especially when students are required to access and use them.  相似文献   

9.
This experimental study was intended to examine whether the integration of game characteristics in the OpenSimulator-supported virtual reality (VR) learning environment can improve mathematical achievement for elementary school students. In this pre- and posttest experimental comparison study, data were collected from 132 fourth graders through an achievement test. The same math problem-solving tasks were provided to the experimental and control groups in the VR learning setting. Tasks for the experimental group involved the game characteristics of challenges, a storyline, immediate rewards, and the integration of game-play in the learning content. Analysis of covariance with the achievement test results indicated a significant effect of game-based learning (GBL) in the VR environment, in comparison with non-GBL in the VR environment, in promoting math knowledge test performance.  相似文献   

10.
Abstract

Assessment and learning analytics both collect, analyse and use student data, albeit different types of data and to some extent, for various purposes. Based on the data collected and analysed, learning analytics allow for decisions to be made not only with regard to evaluating progress in achieving learning outcomes but also evaluative judgments about the quality of learning. Learning analytics fall in the nexus between assessment of and for learning. As such it has the potential to deliver value in the form of (1) understanding student learning, (2) analysing learning behaviour (looking to identify not only factors that may indicate risk of failing, but for opportunities to deepen learning), (3) predicting students-at-risk (or identifying where students have specific learning needs), and (4) prescribing elements to be included to ensure not only the effectiveness of teaching, but also of learning. Learning analytics have underlying default positions that may not only skew their impact but also impact negatively on students in realising their potential. We examine a selection of default positions and point to how these positions/assumptions may adversely affect students’ chances of success, deepening the understanding of learning.  相似文献   

11.
ABSTRACT

The implementation of learning analytics may empower distance learning institutions to provide real-time feedback to students and teachers. Given the leading role of the Open University UK (OU) in research and application of learning analytics, this study aims to share the lessons learned from the experiences of 42 participants from a range of faculty, academic and professional positions, and expertise with learning analytics. Furthermore, we explored where distance learning institutions should be going next in terms of learning analytics adoption. The findings from the Learning Analytics User Stories (LAUS) workshop indicated four key areas where more work is needed: communication, personalisation, integrated design, and development of an evidence-base. The workshop outputs signalled the aspiration for an integrated analytics system transcending the entire student experience, from initial student inquiry right through to qualification completion and into life-long learning. We hope that our study will spark discussion on whether (or not) distance learning institutions should pursue the dream of an integrated, personalised, and evidence-based learning analytics system that clearly communicates useful feedback to staff and students, or whether this will become an Orwellian nightmare.  相似文献   

12.
Abstract

Although it is frequently claimed that learning analytics can improve self-evaluation and self-regulated learning by students, most learning analytics tools appear to have been developed as a response to existing data rather than with a clear pedagogical model. As a result there is little evidence of impact on learning. Even fewer learning analytics tools seem to be informed by an understanding of the social context and social practices within which they would be used. As a result, there is very little evidence that learning analytics tools are actually impacting on practice. This paper draws on research in self-regulated learning and in the social practices of learning and assessment to clarify a series of design issues which should be considered by those seeking to develop learning analytics tools which are intended to improve student self-evaluation and self-regulation. It presents a case study of how these design issues influenced the development of a particular tool: the Learning Companion.  相似文献   

13.
Well-designed game-based learning can provide students with an innovative environment that may enhance students' motivation and engagement in learning and thus improve their learning performance. The purpose of this study was to examine the relationships among elementary school students' flow experience and learning performances. We also investigated the gender and grade differences as well as the types of potential clusters of flow experiences and performance. Thirty-four elementary school students participated in this study. This study conducted correction analysis, difference analysis and a two-stage cluster analysis. The findings suggested that the students with higher flow experiences tended to have higher learning performances. The results of gender differences showed that female students had high performance scores and great flow experiences in the mini-educational game in this study. Moreover, the results revealed that the students of higher grade had significantly higher scores in both performance and flow experience than the students of lower grade. The result of cluster analysis fell into three categories: low performance/low flow experience students, high flow experience students and high performance/high flow experience students. On the basis of our findings, we also proposed suggestions for future game-based learning research.  相似文献   

14.
Socially shared regulation contributes to the success of collaborative learning. However, the assessment of socially shared regulation of learning (SSRL) faces several challenges in the effort to increase the understanding of collaborative learning and support outcomes due to the unobservability of the related cognitive and emotional processes. The recent development of trace-based assessment has enabled innovative opportunities to overcome the problem. Despite the potential of a trace-based approach to study SSRL, there remains a paucity of evidence on how trace-based evidence could be captured and utilised to assess and promote SSRL. This study aims to investigate the assessment of electrodermal activities (EDA) data to understand and support SSRL in collaborative learning, hence enhancing learning outcomes. The data collection involves secondary school students (N = 94) working collaboratively in groups through five science lessons. A multimodal data set of EDA and video data were examined to assess the relationship among shared arousals and interactions for SSRL. The results of this study inform the patterns among students' physiological activities and their SSRL interactions to provide trace-based evidence for an adaptive and maladaptive pattern of collaborative learning. Furthermore, our findings provide evidence about how trace-based data could be utilised to predict learning outcomes in collaborative learning.

Practitioner notes

What is already known about this topic
  • Socially shared regulation has been recognised as an essential aspect of collaborative learning success.
  • It is challenging to make the processes of learning regulation ‘visible’ to better understand and support student learning, especially in dynamic collaborative settings.
  • Multimodal learning analytics are showing promise for being a powerful tool to reveal new insights into the temporal and sequential aspects of regulation in collaborative learning.
What this paper adds
  • Utilising multimodal big data analytics to reveal the regulatory patterns of shared physiological arousal events (SPAEs) and regulatory activities in collaborative learning.
  • Providing evidence of using multimodal data including physiological signals to indicate trigger events in socially shared regulation.
  • Examining the differences of regulatory patterns between successful and less successful collaborative learning sessions.
  • Demonstrating the potential use of artificial intelligence (AI) techniques to predict collaborative learning success by examining regulatory patterns.
Implications for practice and/or policy
  • Our findings offer insights into how students regulate their learning during collaborative learning, which can be used to design adaptive supports that can foster students' learning regulation.
  • This study could encourage researchers and practitioners to consider the methodological development incorporating advanced techniques such as AI machine learning for capturing, processing and analysing multimodal data to examine and support learning regulation.
  相似文献   

15.
Abstract

How can we best facilitate students most in need of learning support, entering a challenging quantitative methods module at the start of their bachelor programme? In this empirical study into blended learning and the role of assessment for and as learning, we investigate learning processes of students with different learning profiles. Specifically, we contrast learning episodes of two cluster analysis-based profiles, one profile more directed to deep learning and self-regulation, the other profile more directed toward stepwise learning and external regulation. In a programme based on problem-based learning, where students are supposedly being primarily self-directed, this first profile is regarded as being of an adaptive type, with the second profile less adaptive. Making use of a broad spectrum of learning and learner data, collected in the framework of a dispositional learning analytics application, we compare these profiles on learning dispositions, such as learning emotions, motivation and engagement, learning performance and trace variables collected from the digital learning environments. Outcomes suggest that the blended design of the module with the digital environments offering many opportunities for assessment of learning, for learning and as learning together with actionable learning feedback, is used more intensively by students of the less adaptive profile.  相似文献   

16.
Game-based learning has been a popular development and recommended as an effective pedagogy in educating new generations of learners. Few studies, however, have demonstrated the efficacy of game-based learning on learners’ academic performance with empirical data. The described learning outcomes of game-based pedagogy within the limited available research are diverse. One prominent explanation is the lack of established guidelines. This paper addresses the issues of game design guidelines through a qualitative phenomenographic perspective of the experience of a group of students designing an educational game utilizing an adapted instructional design (ID) model – the gentry model. The results revealed the participants benefited from the process primarily in two capacities: a significant growth in their knowledge of game design and content knowledge; and great enjoyment and high motivation in the learning process. We conclude ID models with proper adaption and adjustment are effective to provide guidance and improve the efficacy of game-based learning if more ID models will be examined.  相似文献   

17.
Most graduate programs in management require students to carry out a substantive research project. However, few management students have a comfortable command of the statistical techniques needed to realize such quantitative projects. This can lead to student anxiety and stress, which challenges instructors to devise ways to build students’ self-efficacy with statistical analysis. Drawing on game-based learning principles, we developed an exercise to help students in a graduate-level research methods course practice these statistical techniques. Designed around a series of four gamified challenges, students perform basic statistical analyses (correlations, t-tests, and simple linear regression) to solve puzzles and unlock a reward hidden in a mysterious red envelope. We used the exercise on seven occasions (five times in the methods course and twice in a graduate program preparatory course). After launching it in fall 2021, we observed that students were engaged and enthusiastic about the exercise. To ascertain its effectiveness more systematically, we collected data in five subsequent sections using a pretest/posttest design (N = 84) which showed that perceptions of statistics self-efficacy increased following the exercise. We conclude by suggesting that our exercise can be tailored to other learning contexts such as management and statistics-centered courses.  相似文献   

18.
In game-based learning, adaptive scaffolding can enhance the learning of domain-specific skills, known as first-order scaffolding, and self-regulatory skills, known as second-order scaffolding. To design adaptive scaffolding, we need indicators that identify learning opportunities. Therefore we investigated how indicators of performance and self-regulation relate to overall game performance in a medical emergency simulation game. These indicators have the potential to guide the design of adaptive first-order and second-order scaffolding, respectively. Twenty-six fourth-year medical students played 116 game sessions. Using a multilevel model, we investigated the relationship between overall game performance and a range of online and offline measures. For first-order scaffolding, accuracy, systematicity and thoroughness were found to be valid indicators; for second-order scaffolding, high global self-regulatory scores and frequent monitoring were found to be valid indicators. These indicators can be included in future algorithms for adaptive scaffolding in game-based learning.  相似文献   

19.
ABSTRACT

This study aimed to investigate the effect of flipped classrooms integrated with massive open online courses (MOOCs) and game-based learning on the learning motivation and learning outcomes of students from different backgrounds (in terms of gender, grade, self-confidence indicators in mathematics, and roles played in the game-based learning process). Surveys and a semi-structured open questionnaire were used for data collection, including a basic information questionnaire (to understand the participants’ backgrounds), a questionnaire on learning motivation (the Motivated Strategies for Learning Questionnaire, MSLQ), a test of learning achievements in mathematics, and a semi-structured open-ended questionnaire (to understand the learners’ feelings). Quantitative analysis results showed that flipped classrooms integrated with MOOCs and game-based learning can enhance students’ learning motivation and outcomes. Specifically, compared with students with high self-confidence in learning mathematics, students with low and medium levels of self-confidence showed significantly greater improvement in overall learning motivation. Significantly more enhancements were found for the expectation component of “soldiers” (students with relatively lower learning achievements) than for “generals” (students with higher learning achievements). Furthermore, students in the eighth grade showed significantly greater progress in academic performance than did students in the seventh grade.  相似文献   

20.
Scaffolding has proven an especially interesting and promising area for supporting teaching and learning practices. Particular interest has emerged in scaffolding student learning in technology-enhanced environments. In this paper, we discuss how scaffolding is implemented in technology-enhanced environments, provide an overview of scaffolding processes and techniques in various contexts, and then provide empirically based guidelines for designing scaffolding in technological environments. We examine current research to identify two primary design components, cognitive and interface, and suggest how scaffold design might be improved for more effective use by learners. We conclude by identifying practice and research implications.  相似文献   

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