c-E-p-s Journal Center for Educational Policy Studies Journal Revija Centra za študij edukacijskih strategij Vol.1 No4 Year 2011 Editor in Chief / Glavna in odgovorna urednica Igor Radeka - Odjel za pedagogiju, Milena Valencic Zuljan - Pedagoška fakulteta, Sveučilište u Zadru, Zadar, Croatia Univerza v Ljubljani, Ljubljana, Slovenija Pasi Sahlberg - Director General of Center for International Mobility and Cooperation, Helsinki, Editorial Board / Uredniški odbor Finland Michael W. Apple - Department of Educational Igor Saksida - Pedagoška fakulteta, Policy Studies, University of Wisconsin- Madison, Univerza v Ljubljani, Ljubljana, Slovenija Madison, Wisconsin, USA Michael Schratz - Faculty of Education, Cesar Birzea - Faculty of Philosophy, University of Innsbruck, Innsbruck, Austria University of Bucharest, Bucharest, Romania Keith S. Taber - Faculty of Education, Branka Čagran - Pedagoška fakulteta, University of Cambridge, Cambridge, UK Univerza v Mariboru, Maribor, Slovenija Shunji Tanabe - Faculty of Education, Iztok Devetak - Pedagoška fakulteta, Kanazawa University, Kakuma, Kanazawa, Japan Univerza v Ljubljani, Ljubljana, Slovenija Beatriz Gabriela Tomšič Čerkez - Pedagoška Slavko Gaber - Pedagoška fakulteta, fakulteta, Univerza v Ljubljani, Ljubljana, Slovenija Univerza v Ljubljani, Ljubljana, Slovenija Jon Torei Jonasson - School of Education, Grozdanka Gojkov - Filozofski fakultet, University of Iceland, Reykjavik, Iceland Univerzitet u Novom Sadu, Novi Sad, Srbija Teresa Torres Eca - International Society for Jan De Grooe - Professor at the College of Education Through Art (member); collaborates Europe, Bruges, Belgium and at the University with Centre for Research in Education (CIED), of Tilburg, the Netherlands; Government University of Minho, Braga, Portugal Commissioner for Universities, Belgium, Zoran Velkovski - Faculty of Philosophy, SS. Flemish Community; President of the „European Cyril and Methodius University in Skopje, Skopje, Association for Education Law and Policy" Macedonia Andy Hargreaves - Lynch School of Education, Janez Vogrinc - Pedagoška fakulteta, Boston College, Boston, USA Univerza v Ljubljani, Ljubljana, Slovenija Jana Kalin - Filozofska fakulteta, Univerza v Robert Waagenar - Faculty of Arts, Ljubljani, Ljubljana, Slovenija University of Groningen, Groningen, Netherlands Alenka Kobolt - Pedagoška fakulteta, Pavel Zgaga - Pedagoška fakulteta, Univerza v Ljubljani, Ljubljana, Slovenija Univerza v Ljubljani, Ljubljana, Slovenija Bruno Losito - Facolta di Scienze della Formazione, Universita' degli Studi Roma Tre, Revija Centra za študij edukacijskih strategij Roma, Italy Center for Educational Policy Studies Journal Ljubica Marjanovic Umek - Filozofska fakulteta, issn 2232-2647 (online edition) Univerza v Ljubljani, Ljubljana, Slovenija issn 1855-9719 (printed edition) Wolegang Mitter - Fachbereich Publication frequency: 4 issues per year Erziehungswissenschaften, Johann Wolfgang subject: Teacher Education, Educational Science Goethe-Universität, Frankfurt am Main, Publisher: Faculty of Education, Deutschland University of Ljubljana, Slovenia Hannele Niemi - Faculty of Behavioural Sciences, University of Helsinki, Helsinki, Finland Managing editors: Mira Metljak and Romina Mojca Pecek Čuk - Pedagoška fakulteta, Plešec Gasparič / cover and layout design: Roman Univerza v Ljubljani, Ljubljana, Slovenija Ražman / Typeset: Igor Cerar / Print: Littera Picta Ana Pešikan-Avramovic- Filozofski fakultet, © 2011 Faculty of Education, University of Ljubljana Univerzitet u Beogradu, Beograd, Srbija c-E-p-s Journal Center for Educational Policy Studies Journal Revija Centra za študij edukacijskih strategij The CEPS Journal is an open-access, peer-reviewed journal devoted to publishing research papers in different fields of education, including scientific. Aims & Scope The CEPS Journal is an international peer-reviewed journal with an international board. It publishes original empirical and theoretical studies from a wide variety of academic disciplines related to the field of Teacher Education and Educational Sciences; in particular, it will support comparative studies in the field. Regional context is stressed but the journal remains open to researchers and contributors across all European countries and worldwide. There are four issues per year, two in English and two in Slovenian (with English abstracts). Issues are focused on specific areas but there is also space for non-focused articles and book reviews. About the Publisher The University of Ljubljana is one of the largest universities in the region (see www.uni-lj.si) and its Faculty of Education (see www.pef.uni-lj.si), established in 1947, has the leading role in teacher education and education sciences in Slovenia. It is well positioned in regional and European cooperation programmes in teaching and research. A publishing unit oversees the dissemination of research results and informs the interested public about new trends in the broad area of teacher education and education sciences; to date, numerous monographs and publications have been published, not just in Slovenian but also in English. In 2001, the Centre for Educational Policy Studies (CEPS; see http://ceps.pef.uni-lj.si) was established within the Faculty of Education to build upon experience acquired in the broad reform of the national educational system during the period of social transition in the 1990s, to upgrade expertise and to strengthen international cooperation. CEPS has established a number of fruitful contacts, both in the region - particularly with similar institutions in the countries of the Western Balkans - and with interested partners in Eu member states and worldwide. Revija Centra za študij edukacijskih strategij je mednarodno recenzirana revija, z mednarodnim uredniškim odborom in s prostim dostopom. Namenjena je objavljanju člankov s področja izobraževanja učiteljev in edukacijskih ved. Cilji in namen Revija je namenjena obravnavanju naslednjih področij: poučevanje, učenje, vzgoja in izobraževanje, socialna pedagogika, specialna in rehabilitacijska pedagogika, predšolska pedagogika, edukacijske politike, supervizija, poučevanje slovenskega jezika in književnosti, poučevanje matematike, računalništva, naravoslovja in tehnike, poučevanje družboslovja in humanistike, poučevanje na področju umetnosti, visokošolsko izobraževanje in izobraževanje odraslih. Poseben poudarek bo namenjen izobraževanju učiteljev in spodbujanju njihovega profesionalnega razvoja. V reviji so objavljeni znanstveni prispevki, in sicer teoretični prispevki in prispevki, v katerih so predstavljeni rezultati kvantitavnih in kvalitativnih empiričnih raziskav. Še posebej poudarjen je pomen komparativnih raziskav. Revija izide štirikrat letno. Dve številki sta v angleškem jeziku, dve v slovenskem. Prispevki v slovenskem jeziku imajo angleški povzetek. Številke so tematsko opredeljene, v njih pa je prostor tudi za netematske prispevke in predstavitve ter recenzije novih publikacij. Contents 5 Editorial — Iztok Deyetak Focus 11 In-Service Science Teachers' Technological Pedagogical Content Knowledge Confidences and Views about Technology-Rich Environments Samozaupanje učiteljev naravoslovja v njihovo tehnološko-pedagoško znanje in njihova stališča do tehnološko bogatih okolij — Betül TiMUR and Mehmet FAtiH Ta?ar 27 Student Engagement with a Science Simulation: Aspects that Matter Interakcija študentov z naravoslovnimi simulacijami: pomembni vidiki — Susan Rodrigues and Eugene Gyozdenko 45 Exploring the Impact of and Perceptions about Interactive, Self-Explaining Environments in Molecular-Level Animations Študija vpliva in zaznavanja interaktivnih samorazlagalnih okolij animacij molekularne ravni — Dayid a. Falyo, Michael J. Urban, and Jerry P. Suits 63 Visualisation of Animals by Children: How Do They See Birds? Vizualizacija živali pri otrocih: kako vidijo ptiče? — Sue Dale Tunniclieee Varia 8i Building Partner Cooperation between Teachers and Parents Graditev partnerskega sodelovanja med učitelji in starši — Barbara Steh and Jana Kalin Reviews 103 Valenčič Zuljan, M. and Vogrinc, J. (Eds.), Facilitating Effective Student Learning through Teacher Research and Innovation — Barica Marentič Požarnik 107 Tomšič Čerkez, B. and Zupančič, D., Play Space [Prostor igre] — Borut Juvanec 113 List of Referees in Year 2011 Editorial The thematic focus of the fourth issue of the CEPS Journal is visualisation in education. Thus the main purpose of this issue is the presentation of the use of visualisation elements in different areas of education. The submitted papers were mostly from the field of science education, and the review of the manuscripts resulted in only papers from science education being published. Visualisation in education relates to a specific way of teaching and learning content in various subject areas (natural sciences, mathematics, social sciences, languages, art) with the aid of specific images. With the assistance of visualisation elements, so-called visual learning takes place. This encompasses a familiarity with systems of symbols within scientific disciplines and the development of an ability to interpret the meaning of a particular concept with the use of these systems, all of which are presented with some kind of representation. The following content areas are presented in the papers published in this issue of the CEPS Journal: (1) visual representation as a tool for: (a) illustrating concepts, (b) problem solving, (c) explaining ideas, (d) assisting individuals' mental models of concepts and their integration into the individuals' already existing mental scheme of the concepts, and (e) identifying and changing misconceptions; and (2) the importance of different ICT visualisation approaches in the process of learning. Visualisation is used in science education in its broad spectrum, from static physical models and different types of pictures to multimedia animations and interactive simulations of science phenomena. Modern ICT visualisations (animation, simulations and virtual reality) are becoming an increasingly important tool for presenting abstract and complex phenomena that were previously impossible to present to students at different levels of education. These interactive simulations and virtual reality environments can offer students active learning and opportunities to manipulate science phenomena to the level they feel comfortable with while learning science concepts. As Gilbert (2005a) pointed out, the two main roles of visualisation in education are to visually represent science concepts (external visualisation) and the formation of the learners' mental model of the represented concept (internal visualisation). He also stressed that although external visualisation is a more frequent subject of science education research, internal visualisation must also be understood as an important research issue. An important aspect of visualisation in education lies in the fact that textual learning material has a linear structure, and thus offers the least support for developing adequate mental models. Therefore, 2D and 3D visualisation, and especially dynamic representations such as multimedia and interactive simulations supported by modern ICT, offer the learner the greatest support in developing the internal visualisation of science concepts. Visualisation should tell a story in the process of learning. Based on an analysis of science textbook visualisation, Tversky (2005) suggested that two types of visualisations dominate: structure visualisations (diagrams showing the special and conceptual relationship of a specific part of scientific phenomena) and process visualisations (diagrams showing changes in scientific phenomena over time). They also concluded that many representations combine both types in order to show different important aspects of the presented phenomena to the learner. An important aspect of visualisation that is not well researched in the field of science education is the concept of metavisualisation, which can be interpreted as a part of metacognition (Gilbert, 2005b). It can be suggested that future research should be focused not only on the types of external visualisations that are important for learners' understanding of science concepts, but also on the importance of learners' understanding of their mental model forming. Various research strategies should be used to explore these aspects of presentations in science education, especially strategies focusing on qualitative approaches to determining learners' internal visualisation (Vogrinc & Devetak, 2007). Finally, it is important to emphasise that visualisations are an essential part of teaching, understanding and creating scientific ideas (Tversky, 2005), and as such an important and interesting area of science education research. In the present issue of the CEPS Journal, four papers from respected authors from different countries, including Turkey, England, Scotland, Australia and USA, discuss visualisation in science education. The paper by B. Timur and M. F. Tasar entitled In-Service Science Teachers' Technological Pedagogical Content Knowledge Confidences and Views about Technology-Rich Environments presents teachers' confidence in technological pedagogical content knowledge and illustrates their views about using technology-rich environments (TRE) in science instruction, which is an important issue. The authors discuss the importance of computers and related information communication technologies in enabling visualisations of various scientific concepts, natural phenomena and mechanisms by creating technology-rich environments (TRE). It is important that teachers are aware that TRE offer them opportunities to visualise science phenomena that might be difficult or impossible to view, dangerous to conduct experiments about, impractical or too expensive to bring into the classroom, or too messy or time consuming to prepare in a school laboratory. However, they note that science teaching cannot and should not be undertaken entirely by TRE, but that it is nonetheless absolutely imperative for science teachers to know how to integrate technology into science classrooms. This paper addresses challenges faced by in-service science teachers when creating TRE and gives suggestions for successful TRE integration into science teaching. Timur and Tasar present results and discuss findings showing that in-service science teachers have a low level of confidence in using TRE during science teaching. Teachers participating in the study, however, stressed their need for professional development activities regarding the effective and meaningful use of TRE in science teaching. In the second article of the present issue, Student Engagement with a Science Simulation: Aspects that Matter, S. Rodrigues and E. Gvozdenko propose guidelines for forming interactive science simulations. The authors try to illustrate the importance of multimedia technology that affords an opportunity to better visualise complex relationships often seen in chemistry, describing the influence of chemistry simulation design facets on user progress through a simulation. Three versions of an acid-base titration simulation were randomly allocated to 36 volunteers to examine their interactions with the simulation. The impact of design alterations on the total number of interactions and their patterns were analysed according to specific factors, namely: (a) the placement of a feature on the screen, (b) the alignment of the sequence of instructions, (c) additional instructions prior to the simulation, and (d) the interactivity of a feature. The authors also present interactions between individual factors, such as age, prior experience with science simulations and computer games, perception of the difficulty of science simulations, and general subject knowledge, on one hand, and the efficiency of using the simulation, on the other hand. The results show that the centrality of the position of an element significantly affects the number of interactions with the element, that re-arranging the sequence of instructions on the screen in a left-to-right order improves the following of instructions, and that providing users with additional written advice to follow numbered instructions does not have a significant impact on student behaviour. The results also indicate that the interactivity of a feature has a strong positive correlation with the number of interactions with that feature, which warrants a caution about unnecessary interactivity that may hinder simulation efficiency. The authors concluded that neither prior knowledge of chemistry nor the age of the participants has a significant effect on either the number of interactions or the ability to follow on-screen instructions. In the paper entitled Exploring the Impact of and Perceptions about Interactive, Self-Explaining Environments in Molecular-Level Animations, A. Falvo, M. J. Urban and J. P. Suits report on a study of university students' perception of using interactive animations of the submicroscopic level of chemistry concepts in the learning process. Using the mixed method of pedagogical research, the authors also investigate perceptions of the animated learning tool used. ttis study explores principles of cognitive psychology designed to investigate the main effects of treatment and spatial ability and their interaction. tte results show that science majors score more highly than non-science majors in retention measures (i.e., structure and function) but not in transfer. Significant main effects were found for treatment in function questions and spatial ability in structure questions. ttere was a significant interaction between treatment and spatial ability in structure questions. Additionally, the authors of this study reported that participants believed the key and the motion of ions and molecules were the most helpful parts of the animation. tte study also shows that students perceive the animations as being supportive of their learning, suggesting that animations do have a role in science classrooms. tte last contribution to this thematic issue about visualisation in education is entitled Visualisation of Animals by Children: How Do They See Birds?, in which S. D. Tunnicliffe describes pupils' mental models of birds. She emphasises the fact that children learn to recognise animals from their earliest years through actual sightings in their own observations of their world, but also through second-hand representations in various forms of media. Young learners begin with a template specimen, to which they refer when they see another animal that resembles it, naming the animal accordingly. Gradually, they learn to distinguish members of the subordinate category - bird in the case of the present paper - into subcategories. The author examined drawings as a means of accessing students' mental models, and through their interpretation she studied students' representations of both phyla and species. She also used interviews with participants in order to explain the students' drawings. The results show that as children mature they observe more and more details about the birds they see, thus increasing their knowledge not from school but from their own observations outside school. Later in this edition, we find one paper in the Varia section by B. Šteh and J. Kalin, entitled Building Partner Cooperation between Teachers and Parents. The authors present the goals of teacher-parent cooperation, various potential models of establishing mutual cooperation, and conditions for achieving quality interactive cooperation. They discuss the partnership model as the optimal model of interactive cooperation between teachers and parents, as it includes the distribution of expertise and control with the purpose of ensuring optimal education for children. In the second part of the paper, B. Šteh and J. Kalin present findings of an empirical study carried out on a representative sample of Slovene primary schools. Teachers and parents were asked to give their opinions regarding the need for mutual cooperation, to express their view of each other when fulfilling their respective roles, and to state where they perceive the main obstacles to mutual cooperation. The results show that building positive mutual relationships between teachers and parents is a prerequisite for improving successful cooperation. In the third part of the present issue of the CEPS Journals, there are two reviews of monographs. The first book is entitled Facilitating Effective Student Learning through Teacher Research and Innovation (2010) by editors Valenčič Zuljan, M. and Janez, V., published by the Faculty of Education of the University of Ljubljana (ISBN 978-961-253-051-8), and the second is entitled Play Space [Prostor igre] (2011) by Tomšič Čerkez, B. and Zupančič, D., published by the Faculty of Education and the Faculty of Architecture of the University of Ljubljana (ISBN 978-961-253-053-2). Iztok Devetak References Gilbert, J. K. (2005a). Introduction. In J. K. Gilbert (Ed.), Visualisation in Science Education (pp. 1-5). Dordrecht: Springer. Gilbert, J. K. (2005b). Visualization: A metacognitive skill in science and science education. In J. K. Gilbert (Ed.), Visualisation in Science Education (pp. 9-27). Dordrecht: Springer. Vogrinc, J., & Devetak, I. (2007). Ugotavljanje učinkovitosti uporabe vizualizacijskih elementov pri pouku naravoslovja s pomočjo pedagoškega raziskovanja (Exploring the implications of visualisation elements in science education through pedagogical research). In I. Devetak (Ed.), Elementi vizualizacije pri pouku naravoslovja (Visualisation elements in science education) (pp. 197-215). Ljubljana: Faculty of Education. Tversky, B. (2005). Prolegomenon to scientific visualizations. In J. K. Gilbert (Ed.), Visualisation in Science Education (pp. 29-42). Dordrecht: Springer. In-Service Science Teachers' Technological Pedagogical Content Knowledge Confidences and Views about Technology-Rich Environments BeTÜL TiMUR1 AND MeHMET pATiH Ta^AR*2 ^^ Today's computers and related technologies have an important role in enabling visualisations of the workings of various scientific concepts, natural phenomena and mechanisms by creating technology-rich environments (TRE). TRE offner opportunities to science teachers in cases of natural phenomena that might be difficult or impossible to view, dangerous to conduct experiments about, impractical or too expensive to bring into the classroom, or too messy or time consuming to prepare in a school laboratory. However, science teaching cannot and should not be undertaken entirely by TRE. Science teachers need to know how to integrate technology into science classrooms. Measuring science teachers' confidence in technological pedagogical content knowledge (TPCK) and identifying their views about using TRE in science instruction is an important issue. tte present study aims to address challenges faced by in-service science teachers when creating TRE and gives suggestions for successful technology integration into science teaching. tte data were gathered through a TPCK confidence survey and subsequent interviews. tte results show that in-service science teachers have a low level of confidence in using technology during science teaching. tte teachers surveyed stressed their need for professional development activities regarding the efi^ective and meaningful use of TRE in science teaching. Keywords: In-service teachers, Mixed methods research, Teacher confidence, Technological pedagogical content knowledge, Technology-rich environments 1 ^anakkale Onsekiz Mart Üniversitesi, Egitim Fakültesi, C Blok io6, 17100, ^anakkale, Turkey bapaydin@comu.edu.tr 2 *Corresponding author. Gazi Üniversitesi, Gazi Egitim Fakültesi, K Blok 210 06500, Teknikokullar, Ankara, Turkey mftasar@gazi.edu.tr Samozaupanje učiteljev naravoslovja v njihovo tehnološko-pedagoško znanje in njihova stališča do tehnološko bogatih okolij Betül TiMUR IN Mehmet FAtiH Ta^ar* ^^ Danes imajo računalniki in z njimi povezane informacijsko-komunikaci-jske tehnologije (IKT) v t. i. tehnološko bogatih okoljih (TBO) pomembno vlogo pri vizualizaciji različnih naravoslovnih pojmov in pojavov. TBO učiteljem naravoslovja nudijo možnosti prikaza naravoslovnih pojavov, ki jih je težko ali nemogoče videti, nevarno izvajati, so nepraktični ali predragi, da bi se jih prineslo v učilnico, njihovo izvajanje povzroči preveč nereda ali pa so časovno preveč neekonomični, da bi se jih dalo prikazati v šolskem laboratoriju. Kljub temu pa se pouk naravoslovja ne more in tudi ne sme v celoti izvajati s pomočjo TBO. Učitelji naravoslovja morajo poznati smernice učinkovite integracije IKT v pouk. Pri tem je pomembno, da se določi samozaupanje učiteljev naravoslovja v svoje tehnološko-pedagoško znanje in ugotovi njihova stališča do uporabe TBO pri pouku naravoslovja. Cilji te študije so ugotoviti, s katerimi izzivi se srečujejo učitelji naravoslovja med ustvarjanjem TBO, in podati predloge za uspešno integracijo IKT v pouk naravoslovja. Podatki so bili zbrani z uporabo vprašalnika o samozaupanju učiteljev v svoje tehnološko-pedagoško znanje in intervjuji. Izsledki kažejo, da imajo učitelji naravoslovja nizko samozaupanje v znanje o uporabi IKT pri pouku naravoslovja in da poudarjajo pomen profesionalnega razvoja na področju TBO, da bi IKT lahko učinkovito in smiselno vključevali v pouk. Ključne besede: tehnološko bogato okolje, tehnološko-pedagoško znanje, učitelji, samozaupanje učiteljev Theoretical background Towards the end of the last century, we witnessed the beginning of the widespread use of computer technologies in science classrooms, and practically everywhere else, as personal computer hardware with ever higher capacities became affordable to larger populations and applications with enhanced visual characteristics were created with less effort, not only by computer experts but also by science educators. Although not sufficient for all teachers, several initiatives and efforts emerged in order to help science teachers to better understand the associated teaching methodologies and the benefits of technology-rich environments (TRE) in science. In the coming years, computing is expected to become increasingly effective and indispensible in the processes of science, as is expressed in the "Towards 2020 Science" report: "Scientists will need to be completely computationally and mathematically literate, and by 2020, it will simply not be possible to do science without such literacy. This therefore has important implications for education policy right now" (The Science Group, 2006, p. 8). By reviewing existing empirical studies, however, a recent paper (Hew & Brush, 2007) identified 123 barriers faced by teachers. The authors classified these barriers into six main categories: (a) resources, (b) knowledge and skills, (c) institutions, (d) attitudes and beliefs, (e) assessment, and (f) subject culture. In an OECD report entitled "21" Century Learning Environments", the role of schools is specified as follows: "Today, ICT skills - from completing a simple search on the Internet and writing an essay in Word, to cutting a video and designing a Web page - are a prerequisite for entry into the workforce. Schools have an important role to play in providing students with the necessary skills to become tomorrow's knowledge workers" (OECD, 2006, p. 20). In-service science teachers have an important role to play creating successful TRE in science teaching. Science teachers' technological pedagogical content knowledge Technological pedagogical content knowledge (now known as TPCK or TPACK) has become a commonly referenced conceptual framework of teacher knowledge for technology integration within teacher education. TPCK is described as a complex interaction of content, pedagogy and technology, as well as discussion on the successful integration of technology into instruction (Koehler & Mishra, 2008). In recent years, researchers have described TPCK within the framework Schulman's (1986, 1987) description of pedagogical content knowledge (PCK). According to Schulman (1986, p. 9), PCK "goes beyond the knowledge of subject matter per se to the dimension of subject matter knowledge for teaching", thus being the connection and relationship between pedagogy and content knowledge. Researchers have conceptualised PCK in the domain of teaching with technology using different schemes: "Margerum-Lays and Marx (2003) referred to PCK of educational technology, Slough and Connell (2006) used the term technological content knowledge, and Mishra and Koehler (2006) suggested the term technological pedagogical content knowledge (TPCK) - a comprehensive term that has prevailed in the literature" (as referred to and cited in Angeli & Valanides, 2009, p. 155). TPCK can be described as how teachers understand educational technologies and how PCK interacts with technology to produce effective teaching with technology. Table 1 shows the PCK conceptualisations of ten scholars. Mishra and Koehler's (2006) definition of TPCK is that "[it is] the basis of effective teaching with technology, requiring an understanding of the representation of concepts using technologies; pedagogical techniques that use technologies in constructive ways to teach content; knowledge of what makes concepts difficult or easy to learn and how technology can help redress some of the problems that students face; knowledge of students' prior knowledge and theories of epistemology; and knowledge of how technologies can be used to build on existing knowledge to develop new epistemologies or strengthen old ones." On the other hand, Angeli and Valanides (2009) assert that "content, pedagogy, learners, and technology are contributing knowledge bases to TPCK, but knowledge and growth in each contributing knowledge base alone, without any specific instruction targeting exclusively TPCK as a unique body of knowledge, does not imply automatic growth in TPCK". The authors go on to relate ICT to TPCK, defining TPCK in the following manner: "the ways knowledge about tools and their pedagogical affordances, pedagogy, content, learners, and context are synthesized into an understanding of how particular topics that are difficult to be understood by learners, or difficult to be represented by teachers, can be transformed and taught more effectively with ICT, in ways that signify the added value of technology." Table 1: Components of Pedagogical Content Knowledge from different conceptualisations (Van Driel, Verloop & De Vos, 1998; Park & Oliver, 2008). Scholars Knowledge of a c a iB S^ Is ^ g CO e I5 1= r U CO "ca «0 noes t^ C M rt CO e S3 e ^ ess S S t: o U og a Shulman (1987) d PCK d PCK - - d d d Tamir (1988) - PCK PCK PCK - PCK d - d Grossman (1990) PCK PCK PCK PCK - - d - - Marks (1990) - PCK - PCK PCK - PCK - - Smith and Neale (1989) PCK PCK - PCK - - d - - Geddis et al. (1993) - PCK PCK PCK - - u - - Fermandez et a. (1995) PCK PCK u PCK - - PCK PCK - Magnusson et al. (1999) PCK* PCK PCK PCK - PCK - - - Hasweh (2005) PCK PCK PCK PCK - PCK PCK PCK PCK Loughran et al. (2006) PCK PCK - PCK - - PCK PCK PCK PCK: Author(s) include this subcategory as a component of PCK. d: Author(s) place this subcategory outside PCK as a distinct knowledge base for teaching. * Researchers in science education refer to this component as one's "orientation toward teaching". The aim of the study and research questions The present study aims to measure in-service science teachers' TPCK confidences and identify their views about using technology-rich environments (TRE) in science. We also aim to address challenges faced by in-service science teachers in creating TRE, and to give suggestions for successful technology integration in science teaching. The study focuses on the following research questions: 1. What are in-service science teachers' perceived confidence levels in four TPCK constructs (i.e., technological knowledge, technological pedagogical knowledge, technological content knowledge, technological pedagogical content knowledge)? 2. What are in-service science teachers' views, needs and classroom practices regarding TRE? Method Participants A non-random purposeful sample was used to gather data from in-service science teachers. Ninety-five public school science teachers participated in the survey on a voluntary basis. Sample characteristics are summarised in Table 2. Table 2: Participants' characteristics. Participants' characteristics F % Gender Female 44 46.3 Male 51 53.7 Teaching hours per week 10-14 10 10.5 15-19 35 36.8 20-24 38 40.0 25-19 10 10.5 29-34 2 2.1 Number of students in teacher's classroom Less than 20 10 10.5 21-30 60 63.2 31-40 21 22.1 41-50 4 4.2 Teacher's professional experience 1-5 years 17 17.9 6-10 years 35 36.8 11-15 years 23 24.2 16-20 years 13 13.7 More than 21 years 7 7.4 Instruments The TPCK confidence-science instrument has been adapted to Turkish from Graham, Burgoyne, Cantrell, Smith, Clair and Harris (2009). The original survey instrument was created by Graham et al. and consists of 31 Likert-type items. Respondents were asked: "How confident are you in your current ability to complete each of the following tasks?" Responses were given in the form of 6-point Likert-type questions: 1=not confident at all, 2=slightly confident, 3=somewhat confident, 4=fairly confident, 5=quite confident, 6=completely confident (the scale for TCK items also had 0=I don't know about this kind of technology). tte areas of TPCK, TPK, TCK and TK were created by combining the domains of content, pedagogy and technology. tte original instrument contains eight items related to TPCK, seven items related to TPK, five items related to TCK, and 11 items related to TK in order to measure in-service science teachers' TPCK confidence. Survey adaptation steps suggested by Brislin (1970), White and Elander (1992) were used in the present study (as cited in Hall, Wilson, & Frankenfield, 2003). tte steps were: "1) use short and simple language; 2) secure competent translators who are familiar with the issue; 3) have a refinement group for both translations", while the back-translation method was considered to be the preferred method of obtaining a culturally equivalent instrument (Erkut, Alarcon, Garcia Coll, Troop, & Vazguez Garcia, 1999). After translating the instrument into Turkish, a back translation into English was made for checking purposes. First, three native Turkish speakers made their translations independently. Two of the translators hold PhD degrees in science education and the other is a lecturer at the Department of Computer and Instructional Technologies Teaching. tte authors compared these three translations and formed a Turkish version of the instrument for back translation. Second, three back translations into English were made by three independent Turkish individuals with PhD degrees. Finally, the authors compared the three back translations and created the final version of the instrument for the main study. A revised version of the scale was administered to 393 science and technology teachers to determine its validity and reliability. A factor analysis method yielded the construct validity of the scale. Confirmatory factor analysis (CFA) was used to ensure compliance with Turkish culture. tte instrument consisted of 31 items and four dimensions: technological pedagogical content knowledge (TPCK), technological pedagogical knowledge (TPK), technological content knowledge (TCK) and technological knowledge (TK). Reliability analysis of the instrument revealed that the Cronbach-Alpha coefficient was very high (.92) for the whole instrument. tte reliability coefficients of the four sub-dimensions were also very high, at .89, .87, .89 and .86 respectively for the TPCK, TPK, TCK, and TK sub-dimensions (Timur & Ta^ar, 2011). ttese results showed that TPCK confidence can be used in Turkey for measuring the TPCK confidence of in-service teachers. tte sample items for each dimension are given in Table 3 below. Table 3: Sample items of the TPCK confidence survey for each dimension. Sub-factor Sample items - use online animations that effectively demonstrate a specific scientific principle, - help students use digital technologies to organise and identify patterns in scien-TPCK tific data, - use digital technologies that facilitate topic-specific science activities in the classroom, TPK - use digital technologies to motivate learners, - use digital technologies to help in assessing student learning, - use digital technologies that allow scientists to observe things that would otherwise be difficult to observe, - use digital technologies that allow scientists to speed up or slow down the representation of natural events, TCK - create and edit a video clip, - create a basic presentation using PowerPoint or a similar programme. TK Additionally, face to face semi-structured interviews were conducted with four of the participants. Interviews were conducted with two male and two female science teachers. Four questions were asked in order to probe how they create TRE in their classrooms. tte following questions were asked during the interviews: (1) For what purposes do you use computers in teaching science? (2) What are the barriers to TRE in teaching science? (3) How do you currently use computers to support your science teaching? and (4) How do you create TRE in science teaching? Research design Both quantitative and qualitative research methods were used to investigate the level of TPCK confidence. tte instrument was emailed to more than 450 in-service teachers. tte survey was completed and returned by 101 teachers, but six of the respondents were excluded due to missing data. The data were analysed using the Statistical Package for the Social Sciences (SPSS), and semi-structured interviews with the teachers were recorded in audio and transcribed verbatim. tte aim of the interviews was to collect more detailed data from the participants, and to find out the in-service science teachers' views, needs and classroom practices regarding TRE. Qualitative research must show enough detail for the reader to be able to see the case clearly in order for the researcher's conclusion to make sense (Creswell, 1998). Results In order to address the question of the perceived confidence level of inservice science teachers' related to the four TPCK constructs, teachers were asked, "How would you rate your confidence in doing the following tasks associated with technology usage?" ttirty-one items in the areas of technological knowledge (TK), technological pedagogical knowledge (TPK), technological content knowledge (TCK), and technological pedagogical content knowledge (TPCK) were asked, and responses were made on a 5-point scale reflecting the level of confidence. Means were calculated for all items, and the average mean for the four sub-factors is shown in Table 5, while Table 4 shows the ranges of confidence levels formed. Table 4: tte confidence intervals for the Likert scale. Interval Range Confidence Level 1.00-1.79 not confident at all 1.80-2.59 slightly confident 2.60-3.39 somewhat confident 3.40-4.19 fairly confident 4.20-5.00 completely confident Table 5: Summary of descriptive statistics for sub-factors for the question, "How would you rate your confidence in doing the following tasks associated with technology usage?" Sub-Factor Scale Item No. of Items Min. Max. Mean SD Mean SD TPCK 8 8.00 40.00 25.63 7.24 3.20 0.91 TPK 7 11.00 35.00 22.24 5.30 3.18 0.76 TCK 5 5.00 25.00 15.82 4.88 3.16 0.98 TK 11 18.00 55.00 36.62 9.71 3.33 0.88 According to their responses, the teachers asserted that they feel somewhat confident in all of the four sub-factors. However, they asserted that of the four sub-factors they feel most confident in technological knowledge (TKmean=3.33). ^ey feel somewhat confident in their knowledge of how to use technology and how to teach more effectively with technology, as well as to help students meet any specific curriculum content and to use technologies appropriately in their learning. "In other words, merely knowing how to use technology is not the same as knowing how to teach with it" (Mishra & Koehler, 2006). tte second research question was "What are in-service science teachers' views, needs, and classroom practices regarding TRE?" In order to answer this question, five questions were put to 95 in-service science teachers, and semi-structured interviews were conducted with four teachers. In their responses to the questions about TRE, teachers asserted that computer facilities at their schools are not good enough to create TRE, so they generally give computer-based instruction to the whole class. ttey also asserted that almost all teachers require professional development regarding how to use computers in science instruction. There is a need to provide technological pedagogical content knowledge confidence to in-service science teachers in order to create optimally functioning technology enhanced classrooms. Table 6: Descriptive statistics of teachers' views about TRE in science. Computer facilities f % Computer facilities at the school No computers at school 6 6.3 One computer in each class 28 29.7 Computer lab at school 41 43.2 One computer used for several classes 20 21.1 Hours per week of computer-based instruction 1 17 17.9 2 33 34.7 3 17 17.9 4 11 11.6 More than 4 17 17.9 Group size in classes with computer-based instruction One computer for each student 5 5.3 One computer for two students 8 8.4 Small groups 11 11.6 Whole class 71 74.7 Computer-based instruction years 0 10 10.5 1-5 72 75.7 6-10 13 13.8 Need for professional development regarding using a computer for instruction in science Yes 74 77.9 No 21 22.1 Teachers asserted that they use computers for showing animations, simulations, videos and films, and for making representations with PowerPoint during instruction. The barriers to TRE were: lack of access to Internet at school; difficulty in locating and executing technology-rich materials, such as animations, simulations and videos, for every subject; the pre-class planning and preparation required to create TRE; and classroom management problems. Teachers tend to group the whole class for TRE and show animations, simulations and videos using a projector. ttey asserted that they sometimes stop the video or animation and ask the class questions about the subject. One teacher described the current use of computers in his science instruction as follows: I usually use animations or videos in instruction. It is difficult to find visualisations for every subject in science since most science subjects are abstract. I have to spend time preparing in order to create technology-rich science lessons. However, students in my class are highly motivated when I use visualisations in my science teaching. In the last lesson, I used a cartoon animation of blood cells in my class. The whole class watched the animation together and solved a puzzle after the animation. However, sometimes watching a video or animation in a science lesson cannot be different from watching a movie at the cinema. Another teacher described her technology-rich class as follows: I use a projector when I use a computer in my class. I arrange students' seats in the best way for them to see the whiteboard. I start the lesson with brainstorming about the subject then we watch a video or animation. I do not usually have classroom management problems because students are highly motivated when they are watching a video or animation. However, sometimes students find their peers' questions ridiculous or foolish. Conclusions The present study shows that in-service science teachers do not have sufficient TPCK confidence to create TRE in science teaching, and that they need professional development on the use of TRE in science teaching. Teachers need to have confidence to use technology as an enrichment rather than as a replacement in science teaching. Koch (2005, p. 25) emphasises that technology alone cannot help students to learn science. As she explains, a computer can become part of the science learning experience if the child feels a need to use it in learning, and such a need can be created, for example, while exploring what causes different weather conditions. In this case, students can easily access weather reports on the Internet. ttis act makes the computer a useful and meaningful tool in learning. Such use can also be found in many other computer applications (e.g., certain software packages and online resources) that allow students to explore science phenomena in a simulated environment. In a way, access to interactive manipulation of the simulated phenomena forms a science laboratory that allows the child to study and learn at her or his convenience. Successfully integrating technology into science education relies heavily on the development of well-built, coherent professional development programmes that are designed with a clear understanding of how teachers can use technology in their class in the most effective way. Some recent studies have focused on the barriers effecting technology integration, such as limited access to the Internet, classroom size and lack of teacher knowledge about successful technology integration into instruction (Qakir & Yildirim, 2009; Cure & Özdener, 2008). Other research indicates that PD programmes have a positive impact on teacher development of TPACK (Guzey & Roehrig, 2009; Graham et al., 2009; Varma, Husic & Linn, 2008) and can help teachers to successfully integrate technology into their practice (Niess, 2005; Harris, Mishra, & Koehler, 2009). ttere is a need to provide TPCK confidence to in-service science teachers in order to create optimally functioning technology-enhanced classrooms. It is important to devote time and effort to PD programmes, to exploring the cognitive, transformative and pedagogical aspects of adopting educational technology in teaching, rather than merely presenting the hardware and software to be used (Sturdivant, Dunham, & Jardine, 2009). Recent reports of the Turkish Education Association (2009, p. 174) regarding teacher competences assert that both in-service and pre-service teachers need to have technology competences, or so-called technological pedagogical content knowledge. ttey have to know how to integrate technology into their instruction and create effective technology-rich environments. Recent studies of teacher competences in creating TRE show that primary school teachers fail to use instructional software in their lessons, and that most teachers do not even know whether there is any software available in their fields (Kazu & Yavuzalp, 2008). On the other hand, instructional software is inadequate at primary and secondary school level, and the existing instructional software is not aligned with the subjects in the primary and secondary school curriculum. Furthermore, although primary science teachers and secondary physics teachers believe that it is effective to use computers in instruction, they do not know how to do so and need professional development and support in this area (Uzal, Erdem, & Ersoy, 2009). In another study, it is stated that primary school teachers have inadequate competences for using computers in instruction (Balki & Saban, 2009). In light of these results, in our professional development we will focus on the development of in-service science teachers' technological pedagogical content knowledge, and aim at increasing student achievement in primary school science lessons by utilising interactive computer animations in Force and Motion course subjects. 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H., Verloop, N., & De Vos, W. (1998). Developing science teachers' pedagogical content knowledge. Journal of Research in Science Teaching, 35(6), 673-695. Biographical note Betül TiMUR, Assist. Prof., completed her Ph.D. at Gazi University with a thesis on the development of pre-service science teachers' technological pedagogical content knowledge. She has been teaching science education courses including special topics in physics, science-technology-society, and science teaching since 2007. Her main research interests are inquiry based science, place and importance of science process skills, and technological pedagogical content knowledge. Mehmet FatiH Tasar, Assoc. Prof., is a professor of science education. His main research interests are teaching and learning physics, cognitive foundations of learning, and history and philosophy of science. He was involved in the recent curriculum reform efforts in Turkey, which began in 2003 and continues today. He has published in international and national journals and has presented his scholarly works in many international and national meetings. Dr. Tasar is actively involved in science education research and serves as an academic advisor to several masters and doctoral students Student Engagement with a Science Simulation: Aspects that Matter SusAN Rodrigues*1 and Eugene Gvozdenko2 ^^ It is argued that multimedia technology affords an opportunity to better visualise complex relationships often seen in chemistry. ttis paper describes the influence of chemistry simulation design facets on user progress through a simulation. Three versions of an acid-base titration simulation were randomly allocated to 36 volunteers to examine their interactions with the simulation. The impact of design alterations on the total number of interactions and their patterns was analysed for the following factors: (a) the place of a feature on the screen, (b) alignment of the sequence of instructions, (c) additional instruction before the simulation, (d) interactivity of a feature. Additionally, interactions between individual factors, such as age, prior experience with science simulations and computer games, perception of the difficulty of science simulations, and general subject knowledge, on one hand, and the efficiency of using the simulation, on the other hand, were examined. The findings suggest that: (a) centrality of the position of an element significantly affects the number of interactions with the element, (b) re-arranging the sequence of instructions on the screen in left-to-right order improves the following of instructions, (c) providing users with additional written advice to follow numbered instructions does not have a significant impact on student behaviour, (d) interactivity of a feature was found to have a strong positive correlation with the number of interactions with that feature, which warrants a caution about unnecessary interactivity that may hinder simulation efficiency. Surprisingly, neither prior knowledge of chemistry nor the age of the participants had a significant effect on either the number of interactions or the ability to follow on-screen instructions. Keywords: Chemistry, Educational simulations, Learning, Instructions, Interactivity, Simulation design 1 *Corresponding author. School of Health, Community and Education, Northumbria University, UK susan.rodrigues@northumbria.ac.uk 2 Melbourne Graduate School of Education, University of Melbourne, Australia eugeneg@unimelb.edu.au Interakcija študentov z naravoslovnimi simulacijami: pomembni vidiki Susan Rodrigues* in Eugene Gvozdenko Multimedijska tehnologija naj bi nudila možnosti boljše predstavitve kompleksnih odnosov med pojmi, ki se pogosto pojavljajo pri kemiji. Prispevek podaja vpliv dizajna kemijske simulacije na napredek posameznika pri uporabi simulacije. Tri različice simulacije na temo titracije kisline z bazo so bile naključno predstavljene 36 prostovoljcem, da bi raziskali njihovo interakcijo s simulacijo. Vpliv treh različnih oblik dizajna simulacij na skupno število in vzorec interakcij posameznika s simulacijo je bil analiziran glede na: a) mesto elementa na zaslonu, b) položaj zaporedja navodil, c) dodatna navodila pred simulacijo in d) interaktivnost elementa. Dodatno so bile raziskane še povezave med starostjo, predhodnimi izkušnjami z naravoslovnimi simulacijami in računalniškimi igrami, dojemanjem zahtevnosti naravoslovnih simulacij, znanjem kemijskih pojmov in učinkovitostjo študentov pri uporabi simulacij. Ugotovitve kažejo, da: a) centralna postavitev določenega elementa v simulaciji pomembno vpliva na število interakcij s tem elementom, b) razporeditev zaporedja navodil na zaslonu od leve proti desni izboljša sledenje navodilom, c) dodatna pisna navodila uporabnikom, da naj sledijo oštevilčenim navodilom, ni imela pomembnega učinka na vedenje študentov, d) korelacija med interaktivnostjo elementa in številom interakcij s tem elementom je pozitivna, močna in pomembna, kar kaže na to, da je treba biti pri snovanju simulacij previden, da ne omogočamo nepotrebnih interaktivnosti, ki lahko zavirajo učinkovitost simulacije. Presenetljivo je, da predznanje kemije in starost udeležencev nista imela pomembnega vpliva na število interakcij in zmožnost sledenja navodilom na zaslonu. Ključne besede: učenje, kemija, izobraževalne simulacije, oblikovanje simulacij, interaktivnost, navodila Introduction Information communication technology (ICT) has become ubiquitous as it has become more affordable and more powerful (Madden et al., 2005). By 2008, approximately 66% of British homes had Internet connection, (Office for National Statistics, 2008) and in more recent years, a change in connection to the Internet in the form of broadband has reduced the need for homes to have a computer-dedicated line, increased the speed of data transfer, and allowed for increased use of multimedia within web pages. Valentine, Marsh and Pattie (2005) found that the majority of children used their home computer for school work. Over ten years ago, when Rideout, Foehr and Roberts, (1999) asked a representative sample of American children aged 8-18 which medium they would take to a desert island, the preferred choice was a computer with Internet access. Thus it is not surprising that over recent decades, schools, researchers and policy makers have all shown growing interest in the use of ICT to support classroom teaching and learning. As a consequence, we have seen increasing literature reporting on various forms of ICT for science education. This literature has included reporting on the use of audience response systems (Rodrigues, Taylor, Cameron, Syme-Smith, & Fortuna, 2010), dataloggers (Tortosa, Pinto, & Saez, 2008), email (Van derMeij & Boersma, 2002), the Internet (Mackenzie, 2010), modelling (Pallant & Tinker, 2004), simulations (Eilks, Witteck, & Pietzner, 2010), virtual character research (Rebolledo-Mendez, Burden, & de Freitas, 2008) and whiteboards (Redman, McDougal, & Rodrigues, 2010). Within this body of work, one can also find research linking the culture of informal computer games, student interest and the development and design of appropriate ICT for chemistry (see Prensky, 2004; Grimley et al., 2010), as well as work on attitudes (Tondeur, Van Keer, van Braak, & Valcke, 2008). In the present paper, we consider more than just the motivational aspect; we look at the process of engagement and the influence of the design element in terms of supporting cognitive and skill development in science education. Designers' views of learners and their assumptions about learning theories, learning processes and learning practices ensure that content and pedagogy are intertwined before the technology reaches the classroom (Segall, 2004). Consequently, multimedia design for school purposes has been explored and continues to be explored, resulting in a debate about the influence of various factors in supporting or hindering learning. Mayer, Sobko and Mautone (2003) define multimedia learning as the use of at least two different types of media (graphics, audio, video and text) in presenting information. Clarke and Mayer (2003), Ginns (2005) and Moreno (2006) reported a modality principal and suggested that graphical information explained by onscreen text and audio narration led to cognitive overload and was therefore detrimental to learning. In more recent times, studies (see Dunsworth & Atkinson, 2007; Sanchez & Garcia-Rodicio, 2008) suggest that there is no difference in performance based on the presence or absence of audio narration. Eilks et al., (2010) suggested that technology that allows for a seamless interchange between tables, charts, graphs and model displays could support conceptual linking between these representations. Ploetzner, Bodemer and Neudert (2008) suggest that the required high transfer rate may, unfortunately, result in a limited attention span. Testa, Monroy and Sassi (2010) suggest that graphs depicted in textbooks are 'cleaned' of redundant details/irregularities, whereas technology-generated real-time graphs include 'noise', resulting in some learners finding them challenging to interpret. Indeed, the argument pertaining to computer-based graphing exercises has had a long lifespan. For example, the Brasell (1987) study suggested that a delay in display, even if less than 30 seconds, resulted in subduing nearly all students, for they demonstrated less engagement and became preoccupied with procedural issues. However, Beich-ner (1990) suggested that student engagement could be lowered if the software constructed the graphs. Schnotz and Bannert (2003) suggested that picture use in multimedia learning processes may not be beneficial in every case, while Schwartz, Andersen, Hong, Howard and McGee (2004) and Azevedo (2004) suggest the use of non-linear learning environments may result in inadequate metacognitive competencies. Paivio's dual coding theory (2006) suggests that multiple references to information with connections between verbal and nonverbal (imagery) processing improves the learning process. Chandler and Sweller's (1991, 1992) 'split attention' effect (with the learner addressing multiple information sources before trying to integrate the segments to make them intelligible) and their 'redundancy' concept suggest that disparate sources may generate cognitive overload. Paivio (2006), Chandler and Sweller (1991, 1992) may appear to hold contradictory views, but both sets of ideas seem feasible and at present neither explanation has more currency than the other. In light of these various arguments, and given the growing use and production of simulations and animations in school chemistry, we decided to explore the influence of chemistry simulation design facets on user progress through a simulation. It is argued that multimedia technology affords an opportunity to better visualise complex relationships. We were interested in the scope of this opportunity and hence developed the following research questions: • What are the differences in the nature of student interactions associated with an altered simulation design format? • What are the effects of the changes in instruction formats on the process of students' engagement behaviour? • How effective are additional written instructions before the simulation? • How does altering the position of controls on the simulation screen affect students' engagement with the simulation? Method Participants The convenience sample included 57 volunteers from four schools and one tertiary institution. tte data collected did not identify the volunteers on a personal level. ttey were anonymously allocated individual codes when they accessed the website and the different institutions were recognised by the log. tte volunteers were asked to provide their age, gender, science subject (science, chemistry, physics, biology) and class/tertiary level, as well as to indicate their previous ICT experience and complete five multiple choice chemistry questions pre-simulation use and post-simulation use. Fifty-seven volunteers submitted required information and 36 of them interacted with the simulation. tte data collected from the volunteers who submitted questionnaires and actually interacted with a simulation provided were used for the analysis presented in the present paper. Among the 36 participants, there were 19 students aged 13-15 years (second year of secondary school) and 15 students aged 16 and over. Two participants did not indicate their age. ttere were roughly equal numbers of male and female participants (17 females and 16 males) using this simulation. ttree participants did not supply details about gender. Table 1: Descriptive statistics of the sample. Sample description Simulation versions 1 2 3 Gender Male Female Not indicated 5 5 6 1 8 8 0 1 2 13-15 2 7 10 Age 16 and over 3 7 5 Not indicated 1 0 1 Chemistry 0 4 5 Science Physics or Biology 1 2 0 Combination 2 8 8 Not indicated or none 2 0 3 Yes 4 8 11 Playing PC games No 1 5 4 Not indicated 1 1 1 Prior experience in Yes 4 6 12 using simulations in No 1 7 3 Science lessons Not indicated 1 1 1 Research design Professor ttomas Greenbowe (2005) kindly provided access to the code for two of his flash-based simulations (a titration and reactivity of metals) available on the internet as learning resources aimed at introducing college chemistry (general chemistry). We modified the code to create three versions of each simulation and to add a facility for monitoring users' interactions with the simulations. A system was created that randomly allocated one version of the two simulations to each user as they accessed the website. A log of all mouse clicks and interactions with the simulation controls (buttons, sliders, text fields and selection boxes) was generated for each user. tte computer tracked the time that the user spent on each stage and on each particular element of the simulations. ttis behind-the-scenes recording of activity was chosen for three reasons. Firstly, we felt it would be less intrusive, and that it therefore had the potential to generate more reliable data. Secondly, collecting images of school children is increasingly discouraged by local authorities. ttirdly, the url was available for use outside the classroom, and filming its use in that milieu would be impractical. Each user had to complete a pre-simulation questionnaire (specific to the chemistry topic for the simulation being viewed) before being randomly allocated one of three versions of the simulation. After the simulation, they were asked to complete a post-simulation test and a post-questionnaire. tte pre-simulation and post-simulation chemistry questions were based on those found in standard textbooks. However, these questions are not discussed here, as the present paper focuses on patterns of interaction and engagement. Figure 1 provides an overview of the sequence. Figure i: Experimental design. The simulations The simulations we used probably best fit within the Thomas and Hooper (1991) category of 'experiencing simulations'. Experiencing simulations model particular scenarios, allowing students to manipulate factors to see their impact or influence. The simulations we used were representative of many common types of simulations used in school science lessons. However, by selecting an acid-base titration simulation aimed at 'college level' we were able to explore the influence of age and, consequently, prior experience factors on user ability to follow instructions, as while the acid-base titration would be familiar to older students it would be completely novel to the younger students in our sample cohort. The 13-year-old students would have encountered the terms acid and base, but in our experience they would not have conducted a titration during practical or wet-lab work in schools. Our sample also included first-year university chemistry undergraduate students, who almost certainly would have conducted titrations during their senior years at school and during their first year at university. The acid-base titration simulation had three versions: the original version (Version 1), a modified version (Version 2) that included a one paragraph pre-text advising students to pay attention to particular aspects (as can be seen in Figure 2), and another modified version (Version 3) that had altered positions for specific elements on the screen (as can be seen in Figure 3). tte following is the excerpt paragraph that appeared on the webpage before the Version 2 titration simulation loaded: "When you click on the button below you will see a simulation that represents a titration. To make the simulation work you must follow the numbered instructions in sequence. So start with instruction 1, then 2, then 3, etc. Some instructions have tabs. You must place the mouse on the tab and drag it open". In Version 3, a menu tab, also identified with the number 3 on the simulation "Select the Acid and Base", was converted from a 'pull out tab' menu to a fixed position, visible menu. tte position of other items on the screen was also modified so that the sequence of instructions was aligned with a common reading pattern (horizontal sequence of left to right) (Gvozdenko et al., 2010). Figure 2: Titration simulation Versions 1 and 2. Figure 3: Titration simulation Version 3. Data analysis We used one-way unrelated analysis of variance (ANOVA) to determine whether the different versions of the acid-base titration simulation had an impact on how students followed the sequence of instructions. Each simulation version involved a separate and unrelated sample of subjects, so we assumed equal population variation and normal distribution of our random population within the different version cohort. The one-way ANOVA allowed us to deduce the mean for the three versions and then compare these means between the versions. Calculating the one-way ANOVA and the variation between scores meant we could compare the variation between sample means for each simulation version. In the null hypothesis, the assumption was that the mean for Version 1 was the same as the mean for Version 2 and Version 3. However, if the one-way ANOVA showed that the variation between the samples was bigger than the variation in the population, we would have to accept the alternative hypothesis, i.e., that the variation was due to an independent variable. If the variability was statistically significant, the findings would indicate that the independent variable was having an effect. We used SPSS to separate the groups for analysis, creating a grouping variable called simulation, and represented each of the three Versions as 1, 2 or 3. As would be expected, the time required to complete each respective simulation version was entered under a variable named 'Time'. Means and standard deviations were determined for each version, and by using Levene's Test of Homogeneity of Variance we verified that the assumption of homogeneity of variance was met. A modified grounded theory approach (see Strauss and Corbin, 1998) allowed us to group track patterns as they emerged from the logged data: a preliminary reading of the tracks allowed for familiarisation of the whole data set of 36 tracks. At this stage, we suggested explanations, which was followed by a closer reading of the tracks that led to interpreting and coding into themes. To ensure rigour, the data analysis was triangulated. As two independent researchers, we reviewed the data and then reflected on and compared the themes that emerged from our independent analysis. This process helped us to develop perspectives while reducing subjectivity bias. Themes that emerged from the tracks as common or typical, resulting in what van Manen (1990) called 'control and order', allowed us to generate what Polking-horne (1988) called 'plotlines' for the collated tracks. ttese plotlines inform the writing presented in this article. When reviewing the tracking data, we were particularly interested in the nature of actions and steps taken by the users, as we were interested in the nature of engagement with the different versions of the simulation. Tracking their engagement could also tell us about the influence of particular design elements, thus allowing for an evaluation of effectiveness and performance as gauged by the pre-simulation and post-simulation tests. Findings Our findings are based on the tracks generated by student engagement and actions when using a randomly assigned version of the titration simulation. As the simulations were allocated randomly to volunteers, six students completed a pre-survey and engaged with Version 1, while 14 students completed a pre-survey and engaged with Version 2 and 16 students completed a pre-survey and engaged with Version 3. Our findings show that 62% of the participants thought the titration simulation was equally as interesting as a computer game, and 82% believed that science simulations were easy. Hence it could be argued that the students involved were not novices in using simulations, and perceived themselves to be efficient simulation users. Despite this, the tracks showed that, unfortunately, only one participant reached the correct response in the field CALC OK at STEP 6. Positioning instructions and icons An analysis of the tracks showed that if a button that controls the drop-wise addition from the burette is at a more central location it increases the number of interactions with that particular control by approximately 25%. tte analysis also showed that having control elements in a side position decreased the number of interactions. Analysis showed that converting a tab menu (that slid out) into a fixed menu resulted in a decrease in the number of overall interactions, including non-productive interactions, by 30-40%. tte data collected also allows an analysis of the relationship between student responses (in terms of gender, age, computer game experience and simulation user experience) and two measures of their behaviour and activity when using the simulation: (a) the pattern of engagement with the simulation inputs/controls, (b) the total number of interactions between a student and the simulation. A one-way unrelated analysis of variance (ANOVA) found that the simulation version had a significant effect on how students followed the order of the instructions (F2,29=3.69, p<0.05). tte extent to which students followed a recommended sequence of controls was significantly higher among the students using simulation Version 3 (M=4.24, SD=1.43), with 16 students, than for students using simulation Version 2 (M=2.85, SD=1.46), with 14 students. ttis was independent of age or gender. tte extent to which students followed the intended sequence of controls was also higher with students using Version 3 in comparison with students using Version 1 (M=3.20, SD=1.10). However, as indicated previously, the Version 3 and Version 1 comparative finding warrants a degree of care, as there was a smaller number of students (n=6) using Version 1. Contrary to our expectations, prior experience in playing computer games had no significant effect on how students followed the order of the instructions (F1,29=0.132, ^=0.719). However, prior experience in playing games had a significant effect on the number of interactions (F1,29=4.81, ^=0.036), with those students who indicated that they did not play computer games (n=10, M=40, SD=33) having nearly three times fewer interactions than those who indicated that they played computer games (n=21, M=129, SD=23). tte students who had previous experience (n=11, M=68, SD=64) with simulations in a lesson were on average engaged in more interactions with the simulation than those who did not (n=20, M=118, SD=129). ttis effect was not statistically significant. A one-way unrelated analysis of variance (ANOVA) found that prior experience in using simulations in a lesson had a significant effect on how students followed the order of the instructions (F1,29=4.21, p<0.05). Perhaps, as to be expected, the students with no experience in simulation use in classrooms (n=10, M=2.82, SD=1.47) on average followed the order of the controls less efficiently than those with prior experience (n=20, M=3.95, SD=1.54). Student perception of 'easiness' in using a simulation was found to have a significant effect on the number of interactions (F2,24=5.31, p<0.05). tte students who thought that it was "very easy" to use a simulation (n=2, M=336, SD=202) on average had twice as many interactions than those who thought that simulations are "easy" (n=20, M=90, SD= 97) or "not easy" (n=5, M=100, SD=85). The analysis of data showed that age did not have any significant effect on student behaviour patterns (F3,27=0.274, p=0.843). This would suggest that regardless of whether or not the students had previously encountered the chemistry (acid-base titrations) there was no significant effect on behaviour, which would imply prior knowledge of chemistry did not have a significant effect on either the number of interactions or the order in following instructions. Patterns of behaviour Two of the students using Version 1 and two of the students using Version 2 did not appear to pay attention to the 'number sequence' associated with the instructions. ttese numbered instructions were intended to steer them and guide the decisions they made with respect to their process order. What was noticeable was that the proportion of those wrongly following numbered instructions was less for the cohort using Version 2 (simulation with pre-direction) than the cohort using Version 1, but not less than the cohort using Version 3. The difference in behaviour between the three versions showed that 10 of the 14 participants using Version 2, which is over two thirds, had chaotic behaviour patterns. In contrast, only three of the 16 participants using Version 3 had chaotic behaviour patterns, while 11 of those using simulation Version 3 (fixed position openly displayed menu and modified reading pattern) followed the steps sequentially. Interestingly, despite having directions to steer them towards the process sequence order, only one of the participants managed to follow the steps, and 10 of the 14 students who used Version 2 either showed chaotic behaviour or only managed to complete step/instruction 2 in sequence. In addition, three of the participants using Version 2 (which provided pre-direction before they commenced using the simulation) took between 2.5 and 3 minutes to find and operate the sliding tab menu (instruction 3). There appeared to be a similar age distribution across Version 2 and Version 3, so the chaotic patterns were not due solely to age and possible prior experience. In fact, there were five first-year undergraduates using Version 2, and only one of them reached step 4 in simulation Version 2. Conclusion Our findings involve a small sample size, and with this come the usual caveats regarding drawing generalisations. Nevertheless, our findings suggest that simply providing instructions for students to read prior to using a simulation does not necessarily result in the students following the sequence in the simulation as designed. However, if the design is less ambiguous, for example, a 'pull out tab' menu when converted to a fixed position visible menu, the result is better engagement. It seems that additional instructions before a simulation cannot compensate for ambiguity in simulation design: despite being given directions advising them of the process sequence order, most users of the original versions (1 and 2) showed chaotic engagement behaviour tracks. In contrast, the modified Version 3, with a left-to-right and top-to-bottom aligned sequence of menu controls and a fixed visible menu, saw only one fifth of the cohort displaying chaotic behaviour, with most users following the intended sequence. The presence of an interactive component in a simulation needs to be justified by a learning goal. While visual demonstration involving chemical laboratory tools, such as a probe or a thermometer, or a depiction of atom movement in different chemical solutions could aid learning, the interactive sliding out menu tab was a hurdle for some students who clicked multiple times on the tab control. Our findings also show that age did not have any significant effect on the student behaviour patterns. Given that some of the participants were undergraduate degree-level students, this would suggest that regardless of whether or not they had previously encountered acid-base titrations there was no significant effect on engagement behaviour. This implies that prior knowledge of chemistry did not have a significant effect on either the number of interactions or the order in following instructions. These findings suggest that simulation design is therefore crucial if, for example, a simulation is to be used for assessment purposes. For a student may have the requisite subject content knowledge to enable them to undertake a wet-lab practical, but when they encounter a simulated version of that wet-lab practical it may be their ability to engage effectively with the technology that hinders their ability to perform to capacity. 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He has teaching experience in the area of foreign languages and IT in education in secondary and adult education. Research interests include on-line assessment systems. Currently, he works on the SMART project (smartvic.com) which provides diagnostics of students' mathematical thinking and conceptual development. Exploring the Impact of and Perceptions about Interactive, Self-Explaining Environments in Molecular-Level Animations David a. Falvo*1, Michael J. Urban2 and Jerry P. Suits3 ^^ ttis mixed-method study investigates the effects of interactivity in animations of a molecular-level process and explores perceptions about the animated learning tool used. Treatments were based on principles of cognitive psychology designed to study the main effects of treatment and spatial ability and their interaction. Results with students (n=189) showed that science majors scored higher than non-science majors in retention measures (i.e., structure and function) but not in transfer. Significant main effects were found for treatment in function questions and spatial ability in structure questions. ttere was a significant interaction between treatment and spatial ability in structure questions. Additionally, in this study participants believed the key and the motion of ions and molecules were the most helpful parts of the animation. This study shows that students perceive the animations as being supportive of their learning, suggesting that animations do have a role in science classrooms. Keywords: Interactive learning environments, Simulations, Visualisations 1 * Corresponding author. Richard W. Riley College of Education and Leadership Walden University, 155 Fifth Ave. South, Suite 100, Minneapolis, MN 55401 david.falvo@waldenu.edu 2 Professional Education, Campus Box 35, Bemidji State University, Bemidji, MN 56601 3 Chemistry & Biochemistry, Campus Box 98,University of Northern Colorado, Greeley, CO Študija vpliva in zaznavanja interaktivnih samorazlagalnih okolij animacij molekularne ravni David A. Falvo*, Michael J. Urban in Jerry P. Suits Študija, izvedena po kombiniranem raziskovalnem pristopu, je ugotavljala učinke interaktivnosti v animacijah procesa na molekularni ravni in zaznave, povezane s tem animacijskim učnim orodjem. Obravnava učne vsebine je temeljila na načelih kognitivne psihologije, proučevani pa so bili glavni učinki obravnave vsebine in prostorske sposobnosti udeležencev. Rezultati učnega uspeha študentov (n = 189) kažejo, da študentje naravoslovja dosegajo višje rezultate kot študentje nenara-voslovnih ved pri preverjanju pomnjenja vsebine (npr. struktura in funkcija), ne pa tudi pri transferu znanja. Pomembni učinki so bili ugotovljeni pri obravnavi vsebine, kadar so bila vprašanja povezana s funkcijo in prostorskimi sposobnostmi, ne pa tudi pri vprašanjih, povezanih s strukturo. Pomembna povezava pa je med obravnavo vsebine in prostorskimi sposobnostmi, kadar so bila vprašanja povezana s strukturo. Udeleženci raziskave so izrazili, da sta bila legenda ter gibanje ionov in molekul del animacije, ki jim je bil najbolj v pomoč pri učenju. Študija ugotavlja, da študentje dojemajo animacije kot učinkovito podporo pri učenju, zato imajo pomembno vlogo pri pouku naravoslovja. Ključne besede: vizualizacija, interaktivna učna okolja, simulacije Introduction A great deal of research has been conducted about improving students' conceptual understandings of chemistry at three different representation levels (i.e., symbolic, particle and macroscopic levels) (Johnstone, 1993; Gabel, 2005). Nurrenbern and Pickering (1987), Sawrey (1990), and Nakhleh (1993) claim that traditional instruction tends to focus on the symbolic level (see Figure 1) in lectures and the macroscopic level in the laboratory. Research has led to specific design principles for instructional multimedia (Chandler & Sweller, 1991; Mayer, 2001). Words and pictures should be used simultaneously and should be presented close to each other in space, while narration should be provided in audio format. Additionally, visualisations and symbols augment human cognitive capacities and help to convey concepts and information (Tversky, 2001). Figure 1: Image of molecules from salt dissolving in water animation. Historically, there have been problems in the use of animations for teaching. Due to the fact that animations sometimes mislead learners, causing misunderstandings, there has been a history of caution about using these tools for teaching. Viewers often interpret movements of forms and figures in an animation as having causality, relationships and even intentions (Martin & Tversky, 2003; Tasker, 2004; Tversky, 2005). Learners assume that the colours and the shapes reflect the actual reality of the represented items, whereas the shapes and colours are, in fact, either symbolic or an idealisation of time and space relations. When effectively designed and used, these visualisations help to ensure adequate perception and comprehension in the real-world context of student learning (Kelly, 2005; Tasker, 2004; Tversky, 2001; Zacks & Tversky, 2003). Theoretical Framework Several studies of self-explaining environments show the effectiveness of this technique (Chi, 1996, 2000). Two studies have shown that students enhance their mental models when they engage in defining explanations of concepts and processes (Chi, 2000; Chi, DeLeeuw, Chiu, & Lavancher, 1994). In another study, researchers found that having students explain a concept using prior knowledge and cognitive reasoning improved the transfer of knowledge learning about the process (Atkinson, Renkl, & Merrill, 2003). Transfer of knowledge learning is defined as the ability to apply knowledge or skills learned in one context to another context. In addition, several learner characteristics can affect how learners perceive and interact with animation features, and may alter the cognitive load they experience (Cook, 2006). In order to study the spatial ability effect on learning from an animation (Schar & Zimmermann, 2007), students were classified as "high spatial" or "low spatial" (Peters et al., 1995; Vandenberg & Kuse, 1978). High-spatial learners may learn better when visual and verbal information is presented simultaneously rather than successively. Conversely, low-spatial learners may not benefit from this design feature (Mayer & Moreno, 2003). Prior knowledge, a covariate in the present study, can influence the representations processed in working memory and how these representations are organised into coherent mental models (Cook, 2006; Schnotz, 2002). There is a difference between how novices and experts process information from an unfamiliar visual representation. Novices focus on the surface features of their perceptual representation, while experts link this representation to a higher level that involves conceptual understanding of the material. Experts omit irrelevant perceptual information and abstract required information from their relevant prior knowledge. Their long-term memory is organised and retrieved as well-developed schemas (Chi, Glaser, & Rees, 1982). Conversely, novices can be confused by visualisations because they lack the prior knowledge to distinguish between relevant and irrelevant information (Linn, 2003). Research Focus This study investigated the interactive environments in a molecular animation in a classroom setting rather than in a laboratory (Cook, 2006). The animation featured sodium chloride (salt) dissolving in water at the molecular level (Tasker et al., 2002). Students saw structures of solid sodium chloride, water molecules, and the structures that resulted when water molecules dissolved the ionic structures of sodium chloride crystals. ttey witnessed the function of the sodium-chloride ionic attraction that resisted this dissolving process and the opposing function where the water-ion attraction overcomes this resistance to dissolve these ions. The research questions for this study were: • RQ1) Does treatment (i.e., type of interactivity and the self-explaining environment used in the molecular-level animation) affect performance on the dependent variables, which are the post-test knowledge assessments? • RQ2) Does spatial ability (high or low) affect performance on the dependent variables, which are the post-test knowledge assessments? • RQ3) Is there a significant interaction between spatial ability and the treatment (version of the animation) that students engaged with during the study? Method Participants First-year students (n=189) at a Midwestern university participated in the study. These university students were either first-year science majors or elementary education majors. The volunteers were randomly assigned to one of the treatment groups or to the control group. Participants in the qualitative component of the study came from the same pool of individuals. Five females ranging between the ages of 18 and 25 volunteered to take part in the phenomenology with semi-structured interviews (Creswell, 1998). Instruments Students completed a demographic survey about their prior experience in science, as well as providing information about their age, gender and characteristics. Their spatial ability was assessed using the Vandenberg spatial ability assessment (Peters et al.,1995; Vandenberg & Kuse, 1978). Students also took a post-test, which was a knowledge assessment about the topic presented in the animation (i.e., salt dissolution in water at the molecular level). This test included structure and function questions that were used as retention measures. Research design Prior to watching the animation of sodium chloride (salt) dissolving in water (Tasker et al., 2002), students viewed the components of the animation (e.g., see Figure 2), which were detailed on a table within the interface. The first version of the animation was basic, including just the visuals and narration, and students were able to replay the animation. In the second version, students had the option of pausing the animation at any time and were able to replay the animation if they so desired. In the third version, the animation automatically paused at selected points (i.e., segments) in order to create five short sections. At each pause point the viewer/student was prompted to either replay the previous section or to move on to the next section. The viewers also had the ability to, at any time, view any of the five sections in any order. The final version of the animation paused between each of the five sections and students were prompted to self-explain what they were seeing and thinking. They did this in a textual format. Students were allowed to revisit each section of the animation in any order. Treatment: Four versions of an interactive/self-explaining environment tte animations used in this study illustrated the process of sodium chloride (salt) dissolving in water at the molecular level (Tasker et al., 2002). It was modified with Flash to create four different versions based on cognitive principles of instructional design. Students viewed the components of the animation (e.g., see Figure 2) before interacting with one of its four versions. Version 1 - Control (Animation Only) The animation played through from start to finish. Students were able to replay the animation if they so desired. Version 2 - Pause Button. Students had the option of pausing the animation at any time. Students were able to replay the animation if they so desired. Version 3 - Pause Button, and Rewind and Forward Buttons. The animation automatically paused at selected points (i.e., segments) in order to create five short sections. At each pause point, the viewer/student was prompted to either replay the previous section or to move on to the next section. ^e viewer/student also had the ability to, at any time, view any of the five sections in any order. Version 4 -Pace with Self-Explaining Environment. The animation paused between each of the five sections and students were prompted to self-explain what they were seeing and thinking. They did this in a textual format. After submitting their self-explanation, they moved to the next segment of the animation. Students were allowed to revisit each section of the animation in any order. Figure 2: Table of key features in the animation. Using SPSS, a general linear model multivariate ANCOVA was used to determine if any of the groups performed significantly better in the post-test. Using the Wilks' Lambda, the researchers explored three different aspects of the independent variables. The Wilks' Lambda (alpha = .05) measures of the proportion of variance in the combination of dependent variables that is unaccounted for by the independent variable (the grouping variable). The analyses explored the effect of treatment, spatial ability and their interaction on transfer knowledge, understanding of structural components and understanding of functional components. Data regarding whether or not participants were science majors was used as a covariate in the analyses. The researchers used the Tukey test as a post-hoc analysis to maintain a family-wise alpha of .05. This research also entailed a phenomenology with semi-structured interviews (Creswell, 1998). All five interviewees planned to become elementary school teachers and ranged in age from 18 to 25. During the interviews, the researchers asked several questions to identify what participants found helpful and what they liked about the animation. Also, they were asked to consider their diagrammatic sketch from the previous study to establish a sense of what they understood, or to let them enhance their sketch by making it more understandable. Results Using SPSS, the MANCOVA test (Table 1) produced significant results for the model on the structure and function retention dependent variables but not for the transfer variable. For the covariant (science or non-science majors), overall the science majors did better on structure (p = .005) and function (p = .016) dependent variables (Table 2). Table 1: MANCOVA tests of between-subjects effects. Source Dependent Variable Type III Sum of Squares df Mean Square F Sig. structure 109.310 8 13.664 4.496 .000 Corrected Model function 18.095