Shallow strategy development in a teachable agent environment designed to support self-regulated learning

To support self-regulated learning (SRL), computer-based learning environments (CBLEs) are often designed to be open-ended and multidimensional. These systems incorporate diverse features that allow students to enact and reveal their SRL strategies via the choices they make. However, research shows that students' use of such features is limited; students often neglect SRL-supportive tools in CBLEs. In this study, we examined middle school students' feature use and strategy development over time using a teachable agent system called Betty's Brain. Students learned about climate change and thermoregulation in two units spanning several weeks. Learning was assessed using a pretest–posttest design, and students' interactions with the system were logged. Results indicated that use of SRL-supportive tools was positively correlated with learning outcomes. However, promising strategy patterns weakened over time due to shallow strategy development, which also negatively impacted the efficacy of the system. Although students seemed to acquire one beneficial strategy, they did so at the cost of other beneficial strategies. Understanding this phenomenon may be a key avenue for future research on SRL-supportive CBLEs. We consider two hypotheses for explaining and perhaps reducing shallow strategy development: a student-centered hypothesis related to “gaming the system,” and a design-centered hypothesis regarding how students are scaffolded via the system.     

基于自我调节机制的智慧教育系统开发

为了解决现有智慧教育学习环境中教育者与学习者缺乏实时互动,从而造成学习效率低下的问题,在研究了动态和交互式的智慧学习环境中自我调节机制对信息质量、系统质量、服务质量、通信质量、用户满意程度相互影响的基础上,提出了一种具有自我调节机制的智慧教育策略.利用自我调节机制,可对学习者进行充分的个人特质分析,并根据个人的学习进度...     

Helping students help themselves: Generative learning strategies improve middle school students' self-regulation in a cognitive tutor

The current study investigated whether prompting students to engage in generative learning strategies improves students' subsequent judgments of learning and self-regulation. Seventy-eight middle school students in a pre-algebra class completed worksheets in between problem-solving sessions in a computer-based cognitive tutor. Some students were prompted to engage in a generative learning strategy (i.e., writing a summary or writing an explanation for a peer) followed by a judgment of learning (generative group), whereas other students were only asked to make a judgment of learning (control group). Results indicated non-significant levels of judgment accuracy in both groups; however, students in the generative group showed better-calibrated help-seeking behaviors when solving subsequent problems in the tutor. These results suggest that self-regulation can improve in the absence of accurate learning judgments, and that generative learning strategies can facilitate such an improvement. This may be especially true for younger students, who generally demonstrate lower metacognitive awareness.     

依据建构主义理论探索大学英语网络教学模式

提出了结合信息技术,整合课堂教学、自主学习、第二课堂的大学英语网络教学模式。借助网络平台,教师在课堂教学中作为知识传授者的身份逐渐弱化,作为课堂活动组织者的作用日益凸显,课堂教学之外,教师更成为学生自主学习和英语课外活动的监督者和指导者。采用这种网络化的教学模式有利于在大学英语教学中实践建构主义学习理论、提高学生语言应用能力和自主学习能力。     

Learning variables,in-class laptop multitasking and academic performance: A path analysis

This study examines the relationships among learning variables, multitasking, and academic performance. Based on a survey with 176 college students, zero-order correlations were first tested between multitasking behaviors and grade. After identifying the relevant multitasking behavior (i.e., multitasking with laptops in lecture halls), the multitasking pattern was entered into a path analysis in order to understand its impact on grade, in comparison to learning variables. It is found that in-class laptop multitasking has a negative impact on grade, with an effect size similar to the impacts of intrinsic and extrinsic motivations, although in a reversed direction. Furthermore, the path analysis shows that self-regulation behaviors are negatively associated with in-class laptop multitasking, suggesting that we should look at in-class laptop multitasking as lack of self-regulation. Finally, the results indicate that self-efficacy and extrinsic motivation influence self-regulation behaviors, implying that educators and parents need to encourage students' self-regulation of laptop multitasking behaviors through building students' senses of self-efficacy and learning motivations (or employing strategies where laptops are used deliberately as part of class), instead of simply banning laptops in classrooms.     

An exploration of students' strategy use in inquiry-based computer-supported collaborative learning

Abstract The aim of this study is to investigate students' use of cognitive learning strategies in inquiry-based computer-supported collaborative learning (CSCL). A process-oriented interview framework on cognitive activity, self-regulation and motivation, and a coding category for analysing cognitive learning strategies and cognitive self-regulation was developed. The students of an intervention group (n=18) participating in inquiry-based CSCL and a comparison group (n=8) were interviewed six to eight times during the 3 years of the study. The results derived from the mixed-method analysis of altogether 161 interviews were compared between the two groups. The results indicate that the students who participated in the inquiry-based CSCL activities reported deeper-level cognitive strategies such as monitoring, creating representations and sharing information collaboratively. The students of the comparison group reported more surface-level strategies such as memorization. However, the findings concerning the utility of CSCL inquiry on cognitive learning strategies were not uniformly positive. It was found that the students of the comparison group reported significantly more strategies under the category of content evaluation. Nevertheless, the results suggest that computer-supported inquiry-based learning can enhance the use of cognitive strategies that support learning.     

Learning presence as a moderator in the community of inquiry model

This study of over 2000 US college students examines the Community of Inquiry framework (CoI) in its capacity to describe and explain differences in learning outcomes in hybrid and fully online learning environments. We hypothesize that the CoI model's theoretical constructs of presence reflect educational effectiveness in a variety of environments, and that online learner self-regulation, a construct that we label “learning presence” moderates relationships of the other components within the CoI model. Consistent with previous research (e.g., Means, Toyama, Murphy, Bakia, & Jones, 2009; Shea & Bidjerano, 2011) we found evidence that students in online and blended courses rank the modalities differently with regard to quality of teaching, social, and cognitive presence. Differences in help seeking behavior, an important component of self-regulated learning, were found as well. In addition, results suggest teaching presence and social presence have a differential effect on cognitive presence, depending upon learner's online self-regulatory cognitions and behaviors, i.e. their learning presence. These results also suggest a compensation effect in which greater self-regulation is required to attain cognitive presence in the absence of sufficient teaching and social presence. Recommendations for future research and practice are included.     

Learner modeling for adaptive scaffolding in a Computational Thinking-based science learning environment

Learner modeling has been used in computer-based learning environments to model learners’ domain knowledge, cognitive skills, and interests, and customize their experiences in the environment based on this information. In this paper, we develop a learner modeling and adaptive scaffolding framework for Computational Thinking using Simulation and Modeling (CTSiM)—an open ended learning environment that supports synergistic learning of science and Computational Thinking (CT) for middle school students. In CTSiM, students have the freedom to choose and coordinate use of the different tools provided in the environment, as they build and test their models. However, the open-ended nature of the environment makes it hard to interpret the intent of students’ actions, and to provide useful feedback and hints that improves student understanding and helps them achieve their learning goals. To address this challenge, we define an extended learner modeling scheme that uses (1) a hierarchical task model for the CTSiM environment, (2) a set of strategies that support effective learning and model building, and (3) effectiveness and coherence measures that help us evaluate student’s proficiency in the different tasks and strategies. We use this scheme to dynamically scaffold learners when they are deficient in performing their tasks, or they demonstrate suboptimal use of strategies. We demonstrate the effectiveness of our approach in a classroom study where one group of 6th grade students received scaffolding and the other did not. We found that students who received scaffolding built more accurate models, used modeling strategies effectively, adopted more useful modeling behaviors, showed a better understanding of important science and CT concepts, and transferred their modeling skills better to new scenarios.     

Effects of interactivity and instructional scaffolding on learning: Self-regulation in online video-based environments

Online learning often requires learners to be self-directed and engaged. The present study examined students' self-regulatory behaviors in online video-based learning environments. Using an experimental design, this study investigated the effects of a newly designed enhanced video learning environment, which was designed to support or scaffold students' self-regulated or self-directed learning on students' learning behaviors and outcomes. In addition, correspondence between students' self-regulation strategies in traditional learning environments and observed self-regulated learning behaviors in the enhanced video environment were examined. A cross-sectional experimental research design with systematic random assignment of participants to either the control condition (common video) or the experimental condition (enhanced video) was utilized. Undergraduate and graduate students participated in the study (N = 80). Study results indicate that the newly designed enhanced video learning environment was a superior instructional tool than the common video learning environment in terms students' learning performance. In addition, there was correspondence between graduate students' self-reported self-regulation and observed self-regulation, with those high on seeking/learning information and managing their environment/behavior more likely to engage more in interactive note-taking.     

Evaluation of a meta-tutor for constructing models of dynamic systems

Modelling is an important skill to acquire, but it is not an easy one for students to learn. Existing instructional technology has had limited success in teaching modelling. We have applied a recently developed technology, meta-tutoring, to address the important problem of teaching model construction. More specifically, we have developed and evaluated a system that has two parts, a tutor and a meta-tutor. The tutor is a simple step-based tutoring system that can give correct/incorrect feedback on student's steps and can demonstrate steps for students when asked. Because deep modelling requires difficult analyses of the quantitative relationships in a given system, we expected, and found, that students tended to avoid deep modelling by abusing the tutor's help. In order to increase the frequency of deep modelling, we added a meta-tutor that coached students to follow a learning strategy that decomposed the overall modelling problem into a series of “atomic” modelling problems. We conducted three experiments to test the effectiveness of the meta-tutor. The results indicate that students who studied with meta-tutor did indeed engage in more deep modelling practices. However, when the meta-tutor and tutor were turned off, students tended to revert to shallow modelling. Thus, the next stage of the research is to add an affective agent that will try to persuade students to persist in using the taught strategies even when the meta-tutoring and tutoring have ceased.     

Promoting academically productive talk with conversational agent interventions in collaborative learning settings

Research on computer-supported collaborative learning (CSCL) and conversational pedagogical agents has strongly emphasized the value of providing dynamic dialogue support for learners working together to accomplish a certain task. Recently, on the basis of the classroom discourse framework of Academically Productive Talk (APT), a flexible form of conversational agent support has emerged employing APT-based intervention methods so as to stimulate pedagogically beneficial conversational interactions among learning partners. This paper investigates the impact of an APT-based Linking Contributions (LC) intervention mode implemented by a conversational agent in the context of a collaborative activity in higher education. This type of agent interventions encourages students to explicitly externalize their reasoning on important domain concepts building upon the contributions of their partners. Forty-three (43) students collaborated in small groups using a prototype CSCL system to accomplish three different tasks in the domain of Multimedia Learning. Groups were randomly assigned to the treatment or the control condition. In the treatment condition, a conversational agent participated in students' dialogues making LC mode interventions. In the control condition, students discussed without the agent intervening. The results of the study illustrated that the students in the treatment condition engaged in a more productive dialogue demonstrating increased explicit reasoning throughout the collaborative activity. Furthermore, it was shown that the students in the treatment condition outperformed the control students in various measures on knowledge acquisition. Evidence also suggests that students' enhanced learning performance was mediated by the positive effect of the agent intervention mode on students' argumentation. Overall, this study provides insights into how the use of a configurable conversational agent displaying unsolicited LC interventions during students' discourse can be beneficial to collaborative learning.     

Promoting argumentation in primary science contexts: an analysis of students' interactions in formal and informal learning environments

The paper reports on the outcomes of a study that utilized a graphical tool, Digalo, to stimulate argumentative interactions in both school and informal learning settings. Digalo was developed in a European study to explore argumentation in a range of learning environments. The focus here is on the potential for using Digalo in promoting argumentative interactions of students in primary science, first, in a school‐based context of students investigating and learning about electricity, and second, in a hands‐on science discovery centre where students are interacting with different scientific phenomena. Data sources included observations of students using Digalo in the two contexts and the resultant Digalo maps. Analysis of observations focused on students' engagement and interactions, and of Digalo maps in terms of the process and content of argumentation. A previously developed level system was used to evaluate the process of argumentation. The study has revealed some limitations of Digalo as a teaching resource, but has provided insights into ways in which students build their knowledge with the help of Digalo as they interact with each other and with scientific phenomena.     

Enhancing middle school students' scientific learning and motivation through agent‐based learning

Facing students' decreasing motivation to pursue scientific study, schools and educators need to coordinate new technologies with pedagogical agents to effectively sustain or promote students' scientific learning and motivation to learn. Although the provision of pedagogical agents in student learning has been studied previously, it is not clear what benefits the strategy might offer with regard to student motivation. This study proposes an agent‐based mechanism that integrates problem‐solving and inquiry‐based instructions to help students better understand complex scientific concepts and to sustain their motivation to learn science. In this study, a quasi‐experiment was conducted to evaluate the performance and feasibility of our proposed mechanism. The results revealed that the agent‐based mechanism was effective and feasible for enhancing students' learning and motivation to learn. The mechanism was associated with increases in the acquisition of knowledge when compared with the control group. Its effect in promoting and sustaining students' motivation was also statistically significant. Detailed discussions of the findings are provided in this study.     

A multivariate investigation of gender differences in the number of online tests received-checking for perceived self-regulation

The purpose of the study was to investigate whether the number of formative e-tests taken differed by gender, using students' perceived self-regulation levels as a covariate. The sample was 340 teacher candidates reached through purposeful sampling. The study lasted a semester; students were involved in a blended learning environment where classroom lessons supported by self-regulatory e-tests as a part of an online course management system, called MOODLE. It was possible for students to take 10-item online quizzes and 20-item practice tests as many as they wanted. In the analysis, a factorial ANOVA design was applied. Findings indicated a moderate correlation between the number of formative e-tests taken and the perceived self-regulation levels, indicating higher perceived self-regulation levels as the number of formative e-tests increased. By using perceived self-regulation levels as a covariate, the gender differences in the number of e-tests taken were also investigated. According to finding, gender variable did not explain the differences in the compound variable “the number of formative e-tests”. However, after controlling for the effect of perceived self-regulation, the findings were significant. Hence, we can conclude that self-regulated behavior is independent of students' gender; therefore, e-assessments is a self-regulated, technology-based instructional aid in higher education.     

多代理强化学习在智能教学系统中的应用

教学的个性化和智能化是智能教学系统研究的重点和难点。文章采用智能代理技术模拟系统中学生的智能和行为方式,将强化学习理论应用于多代理体,设计了结合资格迹理论的强化学习算法,并用以生成和调整适合于每个学生个体的教学内容和教学策略。多代理体技术实现了教学的个性化,强化学习算法使得教学策略具有智能化。实验结果表明,新的算法较原有算法更为有效。     

融合教育心理学理论的分组教学优化算法

针对分组教学优化算法（group teaching optimization algorithm,GTOA）存在求解精度不高、易陷入局部最优的不足,提出了一种融入教育心理学理论的分组教学优化算法（educational psychology group teaching optimization algorithm,EPGTOA）。在杰出组学生的教师教学阶段融入支架式教学理论,教师在教学过程中帮助学生构建知识体系,更快地提高该组学生的学习能力,从而加强算法的局部搜索能力;在学生学习阶段融入建构主义发展观理论,学生逐渐形成自己独特的认知结构,吸收教师传授的知识,提高学习能力,从而增强算法的全局搜索能力。为验证EPGTOA的有效性,选取21个标准测试函数,将EPGTOA与GTOA和基于信息共享的分组教学优化算法、灰狼算法、蜉蝣算法、飞蛾扑火算法、教与学算法算法进行仿真实验,同时采用Wilcoxon检验和平均绝对误差对改进算法所得的数据进行统计分析,结果表明在5%的水平上是显著的。在算法稳定性、求解精度和收敛速度上,EPGTOA都比GTOA有所增强,尤其在求解高维问题上,改进算法有更好的性能。     

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.     

Drawing on technology: An investigation of preservice teacher beliefs in the context of an introductory educational technology course

This study investigated entering preservice teachers' initial beliefs and ideas with regard to the role of technology in teaching and learning. It also examined specific technology-integrated pedagogical strategies and their potential to help preservice teachers begin to shift from traditional teacher-centered beliefs to a more student-centered mindset. The work was conducted in the context of an introductory educational technology course for preservice teachers in a Mid-Atlantic University in the United States. Data sources included pre- and post-course drawings where participants depicted themselves as technology-using teachers, drawing reflections, and weekly reflective entries submitted in response to a blogging assignment. Findings indicated that preservice teachers enter their training programs with traditional, teacher-centered beliefs about the use of technology and the roles of technology-using teachers and students. Analysis of post-course drawings, however, indicated that participants' beliefs began to shift from largely teacher-centered to more mixed teacher- and student-centered. Analysis of reflective blog entries also demonstrated that participants reflected predominantly on how technology can provide opportunities for students, teachers and parents to collaborate. To a lesser extent, participants reflected on how technology can enhance teaching and learning. Based on these findings, implications specifically related to stand alone technology courses and teacher education programs are discussed.     

Individual and team annotation effects on students’ reading comprehension,critical thinking,and meta-cognitive skills

Many students enter college without the needed skills to be successful. Colleges and universities are seeking instructional interventions to address these needs. Various classes are leveraging web-based social media to provide new instructional technologies that will help students learn. This paper reports on two studies related to the potential of online social annotation for improving teaching and learning in second-semester Freshman English classes. The approach, referred to as the Social Annotation Model-Learning System (SAM-LS), combines various instructional strategies, team-based learning, and a social annotation computer-supported collaborative learning tool, HyLighter, to increase student engagement with selected essays and with classmates. SAM-LS stimulates students to actively monitor their thoughts and compare them to both peers and the instructor (or domain experts). Study 1 showed no significant difference between the SAM-LS approach and a control; however, results appear to be related to confounding factors. Study 2 showed that students achieve better outcomes on measures of reading comprehension and meta-cognitive skill, but not critical thinking, when SAM-LS activities include small team collaborations. The two studies suggest future directions for research and development of SAM-LS and the HyLighter tool.     

示例教学法在计算机实验教学中的应用

针对目前计算机实验教学现状和教学质量不高等问题进行了分析,提出了示例教学法。通过示例,激发学生兴趣,经历欣赏、学习、模仿、掌握、提高、创新若干阶段,将理论和实践紧密结合,更好地帮助学生理解教学内容和培养学生的综合能力。经实践证明,该教学法优于传统的教学方法,较好地提高了计算机实验教学的质量。