The VELscience project: Middle schoolers' engagement in student-directed inquiry within a virtual environment for learning

Schools have long fallen short in helping students to develop the skills necessary to engage in scientific inquiry. Emerging technology-based programs can potentially address this shortfall, but the field lacks clear models of instructional materials capable of doing so. The VELscience project seeks to provide a model for one type of software (virtual environments for learning, or VELs) designed to engage students in student-directed inquiry. In student-directed inquiry, students are given a topic or task, then pose questions, design the investigation, collect and analyze data, draw conclusions and publish their findings. This study examined the effectiveness of this model through observations of middle school students who completed Hurricane Hal, a VEL in which students determine the ecological impact of a natural disaster on a wetlands ecosystem. The results suggest that this program successfully engaged students in student-directed inquiry.     

Students' online interactive patterns in augmented reality-based inquiry activities

Inquiry learning has been developing for years and many countries have incorporated inquiry learning into the scope of K-12 education. Educators have indicated the importance of engaging students in knowledge-sharing activities during the inquiry learning process. In this study, a location-based augmented reality (AR) environment with a five-step guiding mechanism is developed to guide students to share knowledge in inquiry learning activities. To evaluate the effectiveness of the proposed approach in terms of promoting the knowledge sharing behaviors of students, an experiment has been conducted in an elementary school natural science course. The participants were 57 fourth-grade students from an elementary school in Northern Taiwan, divided into an experimental group of 28 students who learned with the AR-based approach and a control group of 29 students who learned with the conventional in-class mobile learning approach. The students' learning behaviors, including their movements in the real-world environment and interactions with peers, were recorded. Accordingly, the learning patterns and interactions of the two groups were analyzed via lag-sequential analysis and quantitative content analysis. It was found that, in comparison with the conventional inquiry-based mobile learning activity, the AR-based inquiry learning activity is able to engage the students in more interactions for knowledge construction. The findings of this study provide guidance for helping teachers develop effective strategies and learning designs for conducting inquiry-based learning activities.     

Integrating computer- and teacher-based scaffolds in science inquiry

Because scaffolding is a crucial form of support for students engaging in complex learning environments, it is important that researchers determine which of the numerous kinds of scaffolding will allow them to educate students most effectively. The existing literature tends to focus on computer-based scaffolding by itself rather than integrating it with teacher support. This study examined students' inquiry learning skills and content knowledge when they utilized a virtual learning environment called Supervolcano: Kikai Caldera. The present study specifically explored how the timing of teacher-based metacognitive scaffolding in combination with different types of computer-based procedural scaffolding affected students’ science inquiry learning. To answer this question, a 2 × 2 factorial design was conducted. One factor examined continuous and faded computer-based procedural scaffolds, and the other factor investigated early and late teacher-based metacognitive scaffolds. Students who received both continuous computer-based procedural scaffolding and early teacher-based metacognitive scaffolding performed best in acquiring scientific inquiry skills. Students using both faded computer-based procedural and early teacher-based metacognitive scaffolding had the worst performance in learning scientific inquiry skills. However, although we applied different types of scaffolding, the results showed no statistically significant difference among the groups' science learning knowledge.     

Leveraging machine-learned detectors of systematic inquiry behavior to estimate and predict transfer of inquiry skill

We present work toward automatically assessing and estimating science inquiry skills as middle school students engage in inquiry within a physical science microworld. Towards accomplishing this goal, we generated machine-learned models that can detect when students test their articulated hypotheses, design controlled experiments, and engage in planning behaviors using two inquiry support tools. Models were trained using labels generated through a new method of manually hand-coding log files, “text replay tagging”. This approach led to detectors that can automatically and accurately identify these inquiry skills under student-level cross-validation. The resulting detectors can be applied at run-time to drive scaffolding intervention. They can also be leveraged to automatically score all practice attempts, rather than hand-classifying them, and build models of latent skill proficiency. As part of this work, we also compared two approaches for doing so, Bayesian Knowledge-Tracing and an averaging approach that assumes static inquiry skill level. These approaches were compared on their efficacy at predicting skill before a student engages in an inquiry activity, predicting performance on a paper-style multiple choice test of inquiry, and predicting performance on a transfer task requiring data collection skills. Overall, we found that both approaches were effective at estimating student skills within the environment. Additionally, the models’ skill estimates were significant predictors of the two types of inquiry transfer tests.     

Group differences in computer supported collaborative learning: Evidence from patterns of Taiwanese students’ online communication

This study explored the differences among online elementary school student groups based on their communication features. Two hundred and ninety-one Taiwanese students, ranging in age from 11 to 12 years old, participated in this study. The students were randomly arranged within-class into three-member groups. Each group was asked to use a collaborative learning system to accomplish a group task generating a shared concept map. The textual discussions in each group during collaboration were collected, coded, categorized, and quantified to profile their communication characteristics. Cluster analysis on the resulting communication characteristics resulted in four types of small student groups, including passive or reticent, frequently off-task, actively participating, and knowledge emphasizing. Most student groups (56%) were found to be relatively passive or reticent. Frequently off-task student groups made a protrusive amount of messages for off-task social purposes. The actively participating student groups were characterized by abundant discussion, particularly for continuing task, managing procedure and coordinating efforts. The distinctive feature of knowledge emphasizing student groups was that they devoted particular attention to task related knowledge. In addition, they performed better in task accomplishment.     

Learning physics through play in an augmented reality environment

The Learning Physics through Play Project (LPP) engaged 6?C8?year old students (n?=?43) in a series of scientific investigations of Newtonian force and motion including a series of augmented reality activities. We outline the two design principles behind the LPP curriculum: 1) the use of socio-dramatic, embodied play in the form of participatory modeling to support inquiry; and 2) progressive symbolization within rich semiotic ecologies to help students construct meaning. We then present pre- and post-test results to show that young students were able to develop a conceptual understanding of force, net force, friction and two-dimensional motion after participating in the LPP curriculum. Finally, we present two case studies that illustrate the design principles in action. Taken together the cases show some of the strengths and challenges associated with using augmented reality, embodied play, and a student invented semiotic ecology for scientific inquiry.     

De-coding Our Scholarship: The State of Research in Computers and Writing from 2003–2008

Since its inception, the field of computers and writing has responded to rapid technological advancements that affect the research, practice, and teaching of writing. A potential consequence of addressing these advancements in teaching and practice, however, may be a reduced focus on foundational, empirical research. To examine the state of research in the field of computers and writing, we assessed the types of research published in four journals (Computers and Composition print, Computers and Composition Online, Kairos, and College Composition and Communication (CCC)) from late 2003/early 2004 to the end of 2008. We explored the state of research by investigating research approaches, design, and modes of inquiry over time. Within this context, we considered author gender, collaboration, and employment of interdisciplinary and mixed methods. We applied criteria from MacNealy (1998) to classify 26% of the computers and writing articles we analyzed as rigorous empirical research. We found a preference for qualitative research designs (56% of articles were qualitative) and, to a lesser degree, mixed methods (29%). While providing a sense of the state of the field as it matures, we conclude by presenting discussion questions on the role of research, research drivers, and ways to increase the quality of research and research reporting. We urge the field to consider the kinds of research we do, teach, and value.     

Properties of Bayesian student model for INQPRO

Employing a probabilistic student model in a scientific inquiry learning environment often presents two challenges. First, what constitute the appropriate variables for modeling scientific inquiry skills in such a learning environment, considering the fact that it practices exploratory learning approach? Following exploratory learning approach, students are granted the freedom to navigate from one GUI to another. Second, do causal dependencies exist between the identified variables, and if they do, how should they be defined? To tackle the challenges, this research work attempted the Bayesian Networks framework. Leveraging on the framework, two student models were constructed to predict the acquisition of scientific inquiry skills for INQPRO, a scientific inquiry learning environment developed in this research work. The student models can be differentiated by the variables they modeled and the causal dependencies they encoded. An on-field evaluation involving 101 students was performed to assess the most appropriate structure of the INQPRO’s student model. To ensure fairness in model comparison, the same Dynamic Bayesian Network (DBN) construction approach was employed. Lastly, this paper highlights the properties of the student model that provide optimal results for modeling scientific inquiry skill acquisition in INQPRO.     

Understanding students' performance in a computer-based assessment of complex problem solving: An analysis of behavioral data from computer-generated log files

Computer-based assessments of complex problem solving (CPS) that have been used in international large-scale surveys require students to engage in an in-depth interaction with the problem environment. In this, they evoke manifest sequences of overt behavior that are stored in computer-generated log files. In the present study, we explored the relation between several overt behaviors, which N = 1476 Finnish ninth-grade students (mean age = 15.23, SD = .47 years) exhibited when exploring a CPS environment, and their CPS performance. We used the MicroDYN approach to measure CPS and inspected students' behaviors through log-file analyses. Results indicated that students who occasionally observed the problem environment in a noninterfering way in addition to actively exploring it (noninterfering observation) showed better CPS performance, whereas students who showed a high frequency of (potentially unplanned) interventions (intervention frequency) exhibited worse CPS performance. Additionally, both too much and too little time spent on a CPS task (time on task) was associated with poor CPS performance. The observed effects held after controlling for students' use of an exploration strategy that required a sequence of multiple interventions (VOTAT strategy) indicating that these behaviors exhibited incremental effects on CPS performance beyond the use of VOTAT.     

The effects of computerized inquiry‐stage‐dependent argumentation assistance on elementary students' science process and argument construction skills

This study proposed a computerized inquiry‐stage‐dependent argumentation assistance and investigated whether this can help improve elementary students' performance in science processes and the construction of quality arguments. Various argumentation assistances were developed and incorporated into each stage of scientific inquiry in a computer‐supported scientific inquiry system. A nonequivalent quasi‐experimental design was adopted to evaluate the effectiveness of this approach. Two intact sixth grade classes (N = 55) participated in this study, and each student used a tablet computer to accomplish the designated inquiry activities. One class of students was arranged to use the stage‐dependent argumentation assistance, and the other used a generic text‐based interface. The findings indicate that students who used the stage‐dependent argumentation assistance could acquire significantly better science process and argument construction skills than those using the generic text‐based interface.     

Enhancing skill in constructing scientific explanations using a structured argumentation scaffold in scientific inquiry

Constructing scientific explanations is necessary for students to engage in scientific inquiry. The purpose of this study is to investigate the influence of using a structured argumentation scaffold to enhance skill in constructing scientific explanations in the process of scientific inquiry. The proposed approach is designed to scaffold the following aspects of argumentation: the argumentation process, the explanation structuring, explanation construction, and explanation evaluation. A quasi-experiment was conducted to examine the effectiveness of the structured argumentation scaffold in developing skill in constructing scientific explanations and engaging in electronic dialogues. A web-based collaborative synchronous inquiry system, ASIS (Argumentative Scientific Inquiry System), was utilized to support students as they worked in groups to carry out inquiry tasks. Two intact sixth grade classes (n = 50) participated in the study. The data show that the ASIS with the structured argumentation scaffold helped students significantly improve their skills in constructing scientific explanations, make more dialogue moves for explanation and query, and use more of all four argument components. In addition, the use of warrants, one of the components of an argument, was found to be a critical variable in predicting students' competence with regard to constructing scientific explanations. The results provide references for further research and system development with regard to facilitating students' construction of scientific argumentation and explanations.     

TAP: a software architecture for an inquiry dialogue-based tutoringsystem

In the tutoring agenda planner (TAP) project, we study the feasibility of implementing the inquiry teaching method of Collins and Stevens (1991) as tutoring software. This paper describes the software architecture for TAP-1-a simple inquiry tutoring shell based on the theory of inquiry teaching. The inquiry teaching style has the objective of teaching scientific reasoning skills through a “localized” sequence of well-planned inquiry dialogue. To complement the “localized” dialogue planning framework inherent in the theory of inquiry teaching, the TAP-1 architecture has adopted the “global” curriculum planning technique. TAP-1 has successfully demonstrated the inquiry teaching style through an inquiry planner within an intelligent tutoring system shell. In addition, PADI-a geography tutor that delivers inquiry teaching style-has been implemented using TAP-1. A group of students performed well in an evaluation activity of the tutor. They also foresaw the potential of TAP for achieving the aim of cultivating scientific thoughts     

Exploring the Understanding and Common Use of Scientific and Everyday Knowledge and Students’ Agency in a Kenyan High School

Abstract

The understanding and applications of scientific and everyday knowledge by high school students was documented among 52 secondary students in Kenya. The study utilized a socio-cultural framework, a pre- and post-data-collecting strategy, and theme building in data analysis. Posttest data showed an increase of claims that referred to the conduct of scientific inquiry or systematic “finding out.” It appears that the content of the lecture prompted students’ to consider using scientific knowledge to solve problems in everyday life. The implications of the study point to a reconsideration of the practices of science education in Kenya and similar contexts.     

Multi-agent simulation of complex heterogeneous models in scientific computing

Electronic protoyping is becoming a part of every scientific inquiry and product design, and is the focus of research in the new scientific field of Computational Science and Engineering. The new grand challenge here is the rapid prototyping of manufactured artifacts and the rapid solution to problems with numerous interrelated elements. This, in turn, requires the fast, accurate simulation of physical processes and design optimization using knowledge and computational models from multiple disciplines in science and engineering. In this paper, we formulate a mathematical and software framework for complex rapid prototyping. Its design utilizes the current computer network infrastructures and high performance computation technologies. Its functionality includes adaptability and intelligence with respect to end-users and hardware platforms. We present the architecture of this framework, named SciAgents, using a multi-agent software model encapsulating a collaborating mathematical method. We also briefly discuss some issues related to legacy software reuse that we faced in the implementation. The design of SciAgents allows wholesale reuse of scientific software and provides a natural approach to parallel and distributed problem solving.     

Scientific workflows for computational reproducibility in the life sciences: Status,challenges and opportunities

With the development of new experimental technologies, biologists are faced with an avalanche of data to be computationally analyzed for scientific advancements and discoveries to emerge. Faced with the complexity of analysis pipelines, the large number of computational tools, and the enormous amount of data to manage, there is compelling evidence that many if not most scientific discoveries will not stand the test of time: increasing the reproducibility of computed results is of paramount importance.The objective we set out in this paper is to place scientific workflows in the context of reproducibility. To do so, we define several kinds of reproducibility that can be reached when scientific workflows are used to perform experiments. We characterize and define the criteria that need to be catered for by reproducibility-friendly scientific workflow systems, and use such criteria to place several representative and widely used workflow systems and companion tools within such a framework. We also discuss the remaining challenges posed by reproducible scientific workflows in the life sciences. Our study was guided by three use cases from the life science domain involving in silico experiments.     

Toward collaboration sensing

We describe preliminary applications of network analysis techniques to eye-tracking data collected during a collaborative learning activity. This paper makes three contributions: first, we visualize collaborative eye-tracking data as networks, where the nodes of the graph represent fixations and edges represent saccades. We found that those representations can serve as starting points for formulating research questions and hypotheses about collaborative processes. Second, network metrics can be computed to interpret the properties of the graph and find proxies for the quality of students’ collaboration. We found that different characteristics of our graphs correlated with different aspects of students’ collaboration (for instance, the extent to which students reached consensus was associated with the average size of the strongly connected components of the graphs). Third, we used those characteristics to predict the quality of students’ collaboration by feeding those features into a machine-learning algorithm. We found that among the eight dimensions of collaboration that we considered, we were able to roughly predict (using a median-split) students’ quality of collaboration with an accuracy between ~85 and 100 %. We conclude by discussing implications for developing “collaboration-sensing” tools, and comment on implementing this approach for formal learning environments.     

What else do college students “do” while studying? An investigation of multitasking

We investigated the frequency and duration of distractions and media multitasking among college students engaged in a 3-h solitary study/homework session. Participant distractions were assessed with three different kinds of apparatus with increasing levels of potential intrusiveness: remote surveillance cameras, a head-mounted point-of-view video camera, and a mobile eyetracker. No evidence was obtained to indicate that method of assessment impacted multitasking behaviors. On average, students spent 73 min of the session listening to music while studying. In addition, students engaged with an average of 35 distractions of 6 s or longer over the course of 3 h, with an aggregated mean duration of 25 min. Higher homework task motivation and self-efficacy to concentrate on homework were associated with less frequent and shorter duration multitasking behaviors, while greater negative affect was linked to longer duration multitasking behaviors during the session. We discuss the implications of these data for assessment and for understanding the nature of distractions and media multitasking during solitary studying.     

Conducting guided inquiry in science classes using authentic, archived, web-based data

Students are often unable to collect the real-time data necessary for conducting inquiry in science classrooms. Web-based, real-time data could, therefore, offer a promising tool for conducting scientific inquiries within classroom environments. This study used a quasi-experimental research design to investigate the effects of inquiry-based instruction coupled with archived online data. Ninety-six preservice teachers in a four-year elementary science teacher-training program participated in this study. The students were enrolled in three sections of the methods course, and these existing groups were randomly assigned to the treatment groups: traditional instruction, traditional instruction supported with a simulation, and inquiry-based instruction with archived online data. Data were collected with structured interviews and analyzed with the constant comparative method and one-way ANOVA. Before the instructional interventions, none of the participants had a scientific understanding of tides, and 15% of the participants had no conceptual understanding of tides at all. After instruction, 72% of the participants who received inquiry-based instruction with archived online data were categorized as having scientific conceptual understandings; 46% of participants who received traditional instruction supported with a simulation were categorized as having scientific conceptual understandings; and 43% of participants who received traditional instruction were categorized as having scientific conceptual understandings. Statistical analyses showed that the group receiving inquiry-based instruction with archived online data performed significantly better than the other two instructional groups. Inquiry-based instruction with archived online data can be used to effectively perform inquiry activities within science classes; it might be used at different grade levels to teach a variety of scientific content.     

A contextual game-based learning approach to improving students' inquiry-based learning performance in social studies courses

Inquiry-based learning, an effective instructional strategy, can be in the form of a problem or task for triggering student engagement. However, how to situate students in meaningful inquiry activities remains to be settled, especially for social studies courses. In this study, a contextual educational computer game is developed to improve students' learning performance based on an inquiry-based learning strategy. An experiment has been conducted on an elementary school social studies course to evaluate the effects of the proposed approach on the inquiry-based learning performances of students with different learning styles. The experimental results indicate that the proposed approach effectively enhanced the students' learning effects in terms of their learning achievement, learning motivation, satisfaction degree and flow state. Furthermore, it is also found that the proposed approach benefited the “active” learning style students more than the “reflective” style students in terms of learning achievement. This suggests the need to provide additional supports to students with particular learning styles in the future.     

计算机课程教学中有效提问探究

有效提问是有效教学的一个重要组成部分,好的提问不仅可以激发学生的学习兴趣,而且更能引导学生的思维动向.在职业学校计算机课程教学中,又该如何灵活地运用提问来提高课堂教学的有效性呢？本文将从课堂提问的目的,课堂提问的艺术和课堂提问的注意点三个方面来加以论述.