s C. Zacharia

Physical and Virtual Laboratories in Science and Engineering Education

The world needs young people who are skillful in and enthusiastic about science and who view science as their future career field. Ensuring that we will have such young people requires initiatives that engage students in interesting and motivating science experiences. Today, students can investigate scientific phenomena using the tools, data collection techniques, models, and theories of science in physical laboratories that support interactions with the material world or in virtual laboratories that take advantage of simulations. Here, we review a selection of the literature to contrast the value of physical and virtual investigations and to offer recommendations for combining the two to strengthen science learning.

Comparing the influence of physical and virtual manipulatives in the context of the Physics by Inquiry curriculum: The case of undergraduate students’ conceptual understanding of heat and temperature

We compare the effect of experimenting with physical or virtual manipulatives on undergraduate students’ conceptual understanding of heat and temperature. A pre–post comparison study design was used to replicate all aspects of a guided inquiry classroom except the mode in which students performed their experiments. This study is the first on physical and virtual manipulative experimentation in physics in which the curriculum, method of instruction, and resource capabilities were explicitly controlled. The participants were 68 undergraduates in an introductory course and were randomly assigned to an experimental or a control group. Conceptual tests were administered to both groups to assess students’ understanding before, during, and after instruction. The result indicates that both modes of experimentation are equally effective in enhancing students’ conceptual understanding. This result is discussed in the context of an ongoing debate on the relative importance of virtual and real laboratory work in phys...

Modeling-based learning in science education: cognitive, metacognitive, social, material and epistemological contributions

Models and modeling are considered integral parts of scientific literacy, reflecting educators’ efforts to introduce and engage students in authentic scientific inquiry through Modeling-based Learning (MbL) approaches in science. Over the years research has developed a considerable amount of knowledge concerning MbL. Our purpose in this paper was to review this research in order to systematize the knowledge accumulated and to provide an overview of what needs to be investigated further. We also took into account and describe the role of the teacher as part of the review. Our review shows that MbL has made cognitive, metacognitive, social, material and epistemological contributions in science education. Furthermore, it reveals that important information is still missing in order to ensure effective implementations of MbL. Future research needs to focus on investigating the learning processes which take place during MbL which result in improvements in student conceptual and epistemological understanding and abilities for scientific inquiry.

The Impact of Interactive Computer Simulations on the Nature and Quality of Postgraduate Science Teachers’ Explanations in Physics

This study investigated how individuals’ construction of explanations—a way of ascertaining how well an individual understands a concept—develops from an interactive simulation. Specifically, the purpose was to investigate the effect of interactive computer simulations or science textbook assignments on the nature and quality of postgraduate science teachers’ explanations regarding physical phenomena in Mechanics, Waves/Optics, and Thermal Physics. The use of simulations or science textbook assignments was implemented according to the Predict–Observe–Explain model and integrated into a one‐semester conceptual survey course in physics for practising science teachers who served as participants in the study. Data were collected through semi‐structured interviews and were analysed using a qualitative content analysis approach. Results indicate that the use of computer simulations along with the application of the Predict–Observe–Explain model had a positive impact on the nature and quality of science teachers’ explanations. They improved science teachers’ ability to generate scientifically accurate explanations and fostered in‐depth advancement in teachers’ search for explanatory scientific information regarding the physical phenomena under investigation. In addition, teachers’ explanations became more elaborate, reflecting cause‐effect reasoning and formal reasoning.

Modeling complex marine ecosystems: an investigation of two teaching approaches with fifth graders

This study investigated acquisition and transfer of the modeling ability of fifth graders in various domains. Teaching interventions concentrated on the topic of marine ecosystems either through a modeling-based approach or a worksheet-based approach. A quasi-experimental (pre‐post comparison study) design was used. The control group (n = 17) received a traditional worksheet-based instruction about ecosystems, whereas the experimental group (n = 16) received an instruction which was based on Stagecast Creator, an object-oriented programming tool, and a set of modeling-based curriculum materials. Paper-and-pencil tests were used both before and after the study to evaluate students’ development of specific modeling skills. The data analysis followed both qualitative and quantitative methods. The findings of the present study indicate that (i) the development of modeling ability was effectively enhanced through the modeling-based approach, since, after instruction, students were able to transfer those aspects to unfamiliar contexts; in contrast, the more traditional worksheet-based approach did not promote the development of the same aspects of the modeling skill; and (ii) Stagecast Creator enabled students to construct, test, revise and validate dynamic computer-based models of a marine ecosystem through building, testing and debugging complex rules, routines and programs for simulating multiple behaviours and processes of marine species.

The Effects on Students’ Conceptual Understanding of Electric Circuits of Introducing Virtual Manipulatives Within a Physical Manipulatives-Oriented Curriculum

This study investigates whether Virtual Manipulatives (VM) within a Physical Manipulatives (PM)-oriented curriculum affect conceptual understanding of electric circuits and related experimentation processes. A pre–post comparison study randomly assigned 194 undergraduates in an introductory physics course to one of five conditions: three experimental conditions with different PM and VM sequences and two control conditions with only PM or VM. Conceptual tests assessed students’ understanding. Instructors’ journals, video data, and interviews provided process-related data. Results showed interplay between manipulative and circuit types. For simple circuits, PM and VM use similarly impacted students’ understanding. However, VM better facilitated understanding than PM for complex circuits: PM users, unlike VM users, encountered process-related problems that prevented development of an appropriate conceptual model because only VM afforded a view of current-flow. When students used VM before PM for complex circuits, they developed the appropriate conceptual model to use in the PM phase.

Objects, Entities, Behaviors, and Interactions: A Typology of Student-Constructed Computer-Based Models of Physical Phenomena

The purpose of this study was to develop a framework for analyzing and evaluating student-constructed models of physical phenomena and monitoring the progress of these models. Moreover, we aimed to examine whether this framework could capture differences between models created using different computer-based modeling tools; namely, computer-based programming environments which, in prior research, were found to differ in various aspects of the models constructed through them. We analyzed 220 computer-based models of physical phenomena developed by two groups of elementary-school students. Using open coding we developed a framework that includes five elements of scientific models that code for representations of: (i) the physical objects; (ii) the physical entities; (iii) the object behaviors; (iv) the interactions among physical objects, physical entities, and object behavior(s); and (v) the accuracy of the phenomenon depiction. The implementation of this framework confirmed that it can differentiate student-generated models according to their sophistication and structural components, independent of the computer-based programming environments used to create the models.

The use of mobile devices as means of data collection in supporting elementary school students’ conceptual understanding about plants

ABSTRACT The purpose of this study was to examine the impact of mobile learning among young learners. Specifically, we investigated whether the use of mobile devices for data collection during field trips outside the classroom could enhance fourth graders’ learning about the parts of the flower and their functions, flower pollinators and the process of pollination/fertilization, and the interrelationship between animals and plants, more than students’ use of traditional means of data collection. For this purpose, we designed a pre–post experimental design study with two conditions: one in which participants used a mobile device for data collection and another using traditional means (e.g. sketching and note-taking). The sample comprised 48 fourth graders (24 in each condition), who studied the flower, its parts, and their functions. A conceptual test was administered to assess students’ understanding before and after instruction. Moreover, the students’ science notebooks and accompanying artifacts were used as a data source for examining students’ progress during the studys intervention. The conceptual test and notebook data were analyzed statistically, whereas we used open coding for the artifacts. Findings revealed that using mobile devices for data collection enhanced students’ conceptual understanding more than using traditional means of data collection.

Using Physical and Virtual Manipulatives to Improve Primary School Students’ Understanding of Concepts of Electric Circuits

The purpose of this study was to investigate the effect of experimenting with physical manipulatives (PM), virtual manipulatives (VM), and a blended combination of PM and VM on primary school students’ understanding of concepts in the domain of electric circuits and whether any possible differences relate to the processes that students engage in during PM or VM experimentation. A pre-post comparison study design was used for the purposes of this study that involved 55 participants assigned to three conditions. The first condition consisted of 18 students that used PM, the second condition consisted of 18 students that used VM, and the third condition consisted of 19 students that used the blended combination of PM and VM. For blending VM and PM the Olympiou and Zacharia (Sci Educ 96(1):21–47, 2012) framework was used. This framework takes into consideration the PM and VM affordances and specifically targets the content of each lab experiment separately. All conditions used the same inquiry-oriented curriculum materials and procedures. A conceptual test was administered to assess students’ understanding before and after teaching. Process-related data were derived from video data. Results revealed that the use of the blended combinations enhanced students’ conceptual understanding in the domain of electric circuits more than the use of PM or VM alone. Differences in the effect emerged because only the blended combination was carrying both of PM’s and VM’s advantageous affordances.

Blending Physical and Virtual Manipulatives in Physics Laboratory Experimentation

Given the importance of laboratory experimentation for science education, many researchers have attempted to investigate and document the value of using Physical Manipulatives (PM; real-world physical/concrete material and apparatus) and Virtual Manipulatives (VM; virtual apparatus and material, which exist in computer-based simulations) in science laboratory experimentation (Finkelstein et al. 2005; Hofstein and Lunetta 2004; Jaakkola et al. 2010; Toth et al. 2009; Triona and Klahr 2003; Winn et al. 2006; Zacharia 2007; Zacharia and Anderson 2003; Zacharia and Constantinou 2008; Zacharia and Olympiou 2011; Zacharia et al. 2008). Comparative studies have also been undertaken in order to identify which of these two modes of experimentation (PM or VM) is the most preferable across several science subject domains (Finkelstein et al. 2005; Klahr et al. 2007; Toth et al. 2009; Triona and Klahr 2003; Zacharia 2007; Zacharia et al. 2008, 2012; Zacharia and Constantinou 2008; Zacharia and Olympiou 2011).