科學傳播與教育的結合:科學教育理念下的電視科學新聞對學習者的科學-覺知、享受、興趣、觀點形成、與理解(AEIOU)之影響
62
0
0
全文
(2) 8V. 8 9. a. e. 5. T. 6. 9. R9. rl. r 9. R. 9. y. e 9. 9. 22 1 r. 30. 9. 8. 9. 9. r. R9. 9. 8. 9. 9 888. 9. 555 9. R. K 9. 8. 8. 9. R. n. c 9. R8. R. S. S. 8. 8. B5. r.
(3) (Educational Science Communication). (Daily Science Communication) (Awareness). (Enjoyment). (Interest). (Understanding). (Scientific Literacy in Media) /. SLiM. O. AEIU 1. (Interest) ≤ .05). (Opinion formation). 2. SLiM. (M = 12.47, SD = 2.42) (t = -2.053, p SLiM. (Understanding). (M = 2.06, SD = 1.01) (t = -2.01, p ≤ .05). 3 (Opinion. formation). 4. (Awareness). AEIOU. (Enjoyment).
(4) Abstract. The purpose of this study was to explore the differences toward learners’ perceived scientific Awareness (A), Enjoyment (E), Interest (I), Opinion Formation (O), and Understanding (U) between science education initiated scientific TV news (i.e., Educational Science Communication, ESC) and general scientific TV news (i.e., Daily Science Communication, DSC). By adopting Scientific Literacy in Media (SLiM) as individual level of science learning in school and media, we divided learners into High/Low SLiM group to investigate deeply. The methodology we used to analyze AEIU was quantitative, and O was qualitative. The results revealed that: (1) For low SLiM learners, scientific interest (I) significantly promoted under Educational Science Communication (M = 12.47, SD = 2.42) (t = -2.053, p ≤ .05). (2) For high SLiM learners, scientific understanding (U) significantly promoted under Educational Science Communication (M = 2.06, SD = 1.01) (t = -2.01, p ≤ .05). (3) For all learners, they used more scientific concepts to support their opinions (O) under Educational Science Communication. (4) For all learners, scientific awareness (A) and enjoyment (E) were not significantly different under Educational Science Communication.. Keywords: Science Communication, AEIOU, Scientific TV News, Scientific Literacy in Media..
(5) Table of Contents Chapter1 Introduction....................................................................................................................... 4 1-1 Background of the Study ........................................................................................................... 4 1-2 Purpose of the Study .................................................................................................................. 6 1-3 Limit of the Study ...................................................................................................................... 7 1-4 Definition of Terms.................................................................................................................... 7 Chapter2 Literature Review ............................................................................................................. 8 2-1 Historical Development of Science Education and Science Communication ........................... 8 2-1-1 Main Differences between Science Education and Science Communication .................... 8 2-1-2 Turning Point to Bridge Science Education and Science Communication ...................... 10 2-2 Broadcast TV News to Bridge Science Education and Science Communication ................... 13 2-2-1 Cognitive Loading Theory – 90 s in Length – Well Structured Content.......................... 13 2-2-2 Multimedia – Computer Simulation/Animation – Learn Complex Scientific Concepts . 15 2-2-3 News Values – Domestic Science Development – Promotion of PUS ............................ 16 2-2-4 Framing – Journalist vs Scientist – Sharing Specialty ..................................................... 17 Chapter3 Methodology .................................................................................................................... 18 3-1 Research Framework ............................................................................................................... 18 3-2 Participants and its background information ........................................................................... 19 3-3 Research Procedure ................................................................................................................. 22 3-4 AEIOU Instrument Development ............................................................................................ 24 3-4-1 Questions Design.............................................................................................................. 24 3-4-2 Validity ............................................................................................................................. 25 3-5 Factor Analysis of A, E, and I.................................................................................................. 25 3-6 Reliability in A, E, I, and U ..................................................................................................... 27 3-7 Data Analysis ........................................................................................................................... 28. 1.
(6) 3-7-1 Simple Linear Regression ................................................................................................ 28 3-7-2 Independent Samples t Test .............................................................................................. 28 3-7-3 Coding Analysis ............................................................................................................... 29 Chapter4 Results .............................................................................................................................. 30 4-1 Simple Linear Regression Results of SLiM ............................................................................ 30 4-2 Independent Samples t Test Results of AEIU .......................................................................... 30 4-3 Coding Analysis of Opinion Formation................................................................................... 34 4-3-1 Q1 “In your opinion, please describe Taipei City’s living conditions and environment” 36 4-3-2 Q2 “When an earthquake hits, is a taller building or a shorter building safer? Describe your opinion.” ............................................................................................................................ 37 4-3-3 Q3 “In your opinion, how might carbon dioxide affect our living environment?” .......... 38 Chapter5 Discussion ........................................................................................................................ 39 5-1 Awareness ................................................................................................................................ 39 5-2 Enjoyment................................................................................................................................ 40 5-3 Interest ..................................................................................................................................... 41 5-4 Opinion Formation .................................................................................................................. 43 5-5 Understanding.......................................................................................................................... 43 Chapter6 Conclusion & Future Research ..................................................................................... 45 6-1 Conclusion ............................................................................................................................... 45 6-2 Future Research ....................................................................................................................... 45 Reference .......................................................................................................................................... 47 Appendix 1. Analysis Version of AEIOU Instrument ................................................................... 51 Appendix 2. The Code Book and Examples .................................................................................. 55 Appendix 3. The Scoring way in Understanding Dimension -Take Q4 for Example ................ 56 Appendix 4. The Example of Coding in Opinion Dimension ....................................................... 57. 2.
(7) List of Figures Figure 1 The illustration of PAS, PUS, SL, and SC. (adopted from Kuan, 2011) ............................ 11 Figure 2 The illustration of cognitive loading theory (address from Cooper, 1998). ........................ 14 Figure 3 Research framework of exploring participants’ AEIOU responses to science. ................... 18 Figure 4. The procedure of instrument development. ........................................................................ 22 Figure 5. The summary of research procedure. ................................................................................. 23 Figure 6 Q1’s percentage of categories from HS and LS participants ............................................... 36 Figure 7 Q2’s percentage of categories from HS and LS participants ............................................... 37 Figure 8 Q3’s percentage of categories from HS and LS participants ............................................... 38. List of Tables Table 1 Descriptive statistics of SLiM ............................................................................................... 20 Table 2 Test of Homogeneity of Variances (N=121)......................................................................... 21 Table 3 Three types of questions in AEIOU questionnaire. ............................................................... 24 Table 4 Factor loadings and Cronbach’s alpha values for the three factors ...................................... 26 Table 5 Cronbach’s alpha standard of internal consistency ............................................................... 27 Table 6 The evolution of instrument’s numbers of items in each dimension through the study. ....... 27 Table 7 Summery of linear regression for SLiM assessment results. ................................................ 30 Table 8 All participants’ comparison of AEIU responses. ................................................................ 31 Table 9 High SLiM participants’ comparison of AEIU responses. ................................................... 32 Table 10 Low SLiM participants’ comparison of AEIU responses. .................................................. 33 Table 11 Opinions formation per person............................................................................................ 35 Table 12 Opinions coding scheme ..................................................................................................... 35 Table 13 The proportion of scientific concepts generated by participants. ....................................... 43. 3.
(8) Chapter1 Introduction 1-1 Background of the Study In an age of technology, we need multiple and reliable scientific views to face a complicated and rapidly changing society. As the skin of culture helps the public obtain new ideas and be aware of the changing world (Kerckhove, 1995), the media should try to consider ways of communication because the function of media is not only to deliver scientific information, but also to shape scientific information (Dimopoulos & Koulaidis, 2002). If the media communicate scientific information properly, it should promote public’s ability of judging scientific information and making opinions when some scientific issues was broadly discussed, furthermore, lead the public to active participation of policy-making about science and technology (Chin & Chen, 2007. Norris &. Phillips, 2003). On the contrary, if there is any inaccurate scientific information adopting wrong theory or communicating twisted concepts, it will seriously affect the public’s science literacy (Chin & Chen, 2007).. However, the public in Taiwan have been soaked in a media environment filled with information that has been too subjective or incomplete for a long time (Wu, Chang, Liu, Wu, Lei & Lu, 2015). Huang & Chien (2010) described the fact that Taiwan’s media usually used single perspective approaching different social scientific issues. And sometimes the direction of reporting tends to focus on politics or entertainment. This may distract the public’s attention from scientific substance of issues (Hsieh, 1992). As a result, Huang & Chien (2006) said there is very low amount of domestic news that can motivate public to engage in decision-making about science and technology policy. Therefore, it’s not an abnormal situation that Taiwanese rarely engaged in procedure of scientific decision-making and argued announced decisions with government afterward. These phenomena reflect the need to rethink the way of communicating science in the media.. 4.
(9) In response to demand, the “Different Science News” (Wu, et al., 2015) program tried to make up for the present deficiencies in Taiwan’s media. Considering the easiest way for public to reach scientific information, the program’s producer chose the form of broadcast news. This program is featured by its special cooperating with the media (e.g., news production) and science education (e.g., instructional designer and scientist). This model of producing scientific news is different from tradition, which dominated by the media. In contrast, it combined two field’s specialties to share what science education cares most about is to carefully curate scientific and instructional content for the public’s understanding with TV news media, which is good at exposing stories vividly in order to motivate audiences to watch. We named this kind of science news “Educational Science News” (ESN) in the following. Here comes the question: what will be the effect on the audience after Educational Science News is infused into our Daily Science Communication (DSC) (e.g., the definition of Educational Science Communication in this study, ESC) ? What evaluation framework can be adopted in order to explore these effects? Is there any possibility that the audience’s different backgrounds about science will produce different effects? Burns, O'Connor & Stocklmayer’s work (2003) defined science communication as the use of the appropriate skills, media, activities, and dialogue to produce one or more of the following personal responses to science (the AEIOU vowel analogy): Awareness (A), Enjoyment (E), Interest (I), Opinion-formation (O), and Understanding (U). In other words, the content of science communication not only helps the public “understand” scientific knowledge, but also help the public create one or more literal functios such as “awareness”, “enjoyment”, “interest”, or “opinion-formation” responses to science. These five aims (AEIOU) provided a sharing goal with science communication and science education, giving us the foundation for further research and evaluation. It is a suitable framework to develop research tools in this study to investigate the different effects between Daily Science Communication (DSC) and Educational Science Communication (ESC).. 5.
(10) 1-2 Purpose of the Study The aim is to explore the different of participants’ AEIOU responses under Daily Science Communication and Educational Science Communication. Since the participants’ original science background may cause different responses to science in this study, we will adopt the assessment of SLiM (Rundgren, C. J., Rundgren, Tseng, Lin & Chang, 2010), and also investigate participants’ responses to science by dividing them into High/Low SLiM assessment results. Through these results, we can gain a preliminary outcome of what educational science communication promotes and examine if it has potential to make up the present deficiencies in Taiwan’s media. Through these results a future can be created where there is an effective science communication environment where the public not only learn about and appreciate science but are also willing to engage in science. To achieve those aims, we will examine three research questions:. (1) Can SLiM assessment be used to predict participants’ AEIU responses in this study?. (2) Whether there is a difference on the outcomes of AEIU dimensions between participants in the DSC group and ESC group?. Whether there is a difference on the outcomes of AEIU dimensions between participants in the DSC and ESC groups while dividing them into high and low SLiM assessment results?. (3) Whether there is a difference of the concept generation (i.e., Opinion formation: O) between participants in the DSC group and ESC group?. Whether there is a difference on the concept generation between participants in the DSC and ESC groups while dividing them into high and low SLiM assessment results?. 6.
(11) 1-3 Limit of the Study The research tool we created to explore participants’ AEIOU responses to science may differ from definition to definition and is dependent on the researcher. Furthermore, the target audience of “Different Science News” program is for adults, whose age range is effectively anything above the age of 15 years old. However, results in this study may only reflect part of the public in society and especially those aged 18-25.. 1-4 Definition of Terms (1) Daily Science Communication (DSC): A contemporary environment in which the public is exposed to science-related information, education, media, activities and so on in daily life.. (2) Educational Science Communication (ESC): A setting environment in which 30 minutes clips of educational science news infused into daily science communication.. (3) Educational Science News (ESN): A science news in which its idea of production combines multiple views of science educators, scientists, and media producers. (4) Awareness (A): Being aware of the development of science and scientific methodology, and having positive attitudes toward science. (5) Enjoyment (E): The current modern, convenience and developed technology that brings forth enjoyable life experiences and appreciation. (6) Interest (I): A desire that tends to dig further or pay more attention to scientific issues or activities. (7) Opinion formation (O): A science-related concept formed in the public’s reflection to support their own opinions. (8) Understanding (U): A comprehension of scientific concepts gained.. 7.
(12) Chapter2 Literature Review 2-1 Historical Development of Science Education and Science Communication The study of science education that emerged in the mid-19th century focused on individual teaching, thinking, and learning (Bransford, Brown, & Cocking, 2000). In order to tie a liberal education with the advancement of science (Layton, 1986), it was important to define and offer the best science curriculum (Cuban, 1999; DeBoer, 1991). On the other hand, science communication originally evolved as a practice within the natural sciences communities of the 1970s. During these early stages, science communication formed its own publications and networks for idea-sharing rather than joining networks of more mature and related social sciences. As science journalism grew in the mid-20th century, journalism educators and researchers began to explore issues of science communication (Friedman, Dunwoody, & Rogers, 1986; Krieghbaum, 1957,1967).. 2-1-1 Main Differences between Science Education and Science Communication Both of these two fields shared the overarching goal of helping non-experts and non-members of the professional science community develop knowledge of the content and processes of scientific research (Davis & Russ, 2015). However, the individual development of each field still leads to several main differences between science education and science communication. Baram-Tsabari & Osborne (2015) referred to three main differences. The first is the emphasis that they place on educating, entertaining and engaging to the public. The priority for science education is, not surprisingly, education, entertainment and engagement. As for the field of science communication, it is engagement that is the priority. Secondly, the critical view of science and scientists also differ in these two fields. Science education tends to take the position of “what science says” and “how scientists do things” as truth to show to students what should they learn to educate the next. 8.
(13) generation of scientists. However, “what science says” is only one of many types of potentially relevant knowledge in the field of science communication. “How scientists do things” is an incomplete way of making sense of the world because scientists are concerned with only one type of science communicators who work with young people to engage in science (Baram-Tsabari & Osborne, 2015). Furthermore, in the context of the formal (school) versus informal (media) education, the environment has strongly affected the possible methods and the subjects of study. The causes of the differences above between the two fields might find its origin from the conceptualizations of the process by which “public knowledge of science” comes to be (Davis & Russ, 2015). Educating is the emphasis in science education and has assumed that the public knowledge of science is achieved through the separable processes of teaching and learning. Science educators and researchers have had many productive discussions about what should be learned (e.g., scientific facts, scientific practices, the nature of science) and how it should be taught (e.g., discussion based, inquiry method, project-based science, constructionist). While many science communication researchers frown at the very thought of studying science communication from an educational perspective, they see the communication of a new public knowledge about science more as a dialogue between scientists and the society. Since the 1990s, there has been a shift in science communication research and practice from what has been called deficit models to engagement models (Wynne, 1996; Sturgis & Allum, 2004). The one-way transmission deficit model parallels a tacit view of science education based on an “assembly line instruction” model in which teachers “deliver” information to students who absorb it (Rogoff, Paradise, Arauz, Correa-Cha´vez, & Angelillo, 2003). However, science communicators desired to move away from delivery-oriented models to dialogue-oriented model. In this point of view, science communicators think the public can make more meaningful science-related decisions when facing scientific issues featuring a binary choice model between denial or unquestioning acceptance that arise in the domain of society, such as GMO foods. The public should engage in. 9.
(14) dialogue with teachers or scientists rather than just being delivered by them to gain more knowledge (Baram-Tsabari & Osborne, 2015).. 2-1-2 Turning Point to Bridge Science Education and Science Communication Ever since Paul DeHart Hurd created the term of “scientific literacy” (DeHart, 1958), it has been an ever present theme. Both science education and science communication are motivated by scientific literacy and have shared goals. Through scientific literacy both fields started to have some conversations between them. A review of educational history shows us that since scientific literacy was introduced to the world, the goal of science education has no longer just for cultivating professional scientists. Rather, a part of science education has turned its goal into a general education purpose and not just preparing for professional science and technology careers (DeBoer, 2000). Douglas Roberts (2007) also described that there existed two “visions” in science education. The first vision focuses only on the education of future scientists. This vision pays little attention to what the majority of students need to know about science, resulting in science curricula originally designed to prepare only a minor part of the age group for future academic studies (Abrahams & Millar, 2008). The second vision, according to Roberts (2007), is one of science education designed for all citizens, therefore, its curricula better reflects the goal of creating a science education that is meaningful for all individuals. As for science communication, its original study subjects mostly focused on non-expert citizens, and its study purposes were in line with the concept of scientific literacy. However, the terms in science communication usually used are synonym for “Scientific literacy” (SL), such as “Public awareness of science” (PAS) widely used in Australia, “Public understanding of science” (PUS) in the UK, and “Scientific culture” (SC) in most European nations. Burns et al (2003) reviewed related papers and explained these terms as following:. 10.
(15) (1) Public awareness science (PAS) aims to stimulate awareness of, and positive attitudes (or opinions) towards science (Gilbert, Stocklmayer, and Garnett, 1999). (2) Public understanding of science (PUS) as the name suggests, focuses on understanding science: its content, processes, and social factors (Miller, 1996). (3) Scientific literacy (SL) is the ideal situation when people are aware of, interested and involved in, form opinions about, and seek to understand science (Shen, 1975). (4) Scientific culture (SC) is a society-wide environment that appreciates and supports science and scientific literacy. It has important social and aesthetic (affective) aspects (Godin and Gingras, 2000).. Figure 1 The illustration of PAS, PUS, SL, and SC. (adopted from Kuan, 2011) According to the definition above, it is apparent that though the terms PAS, PUS, SL, and SC should not be used interchangeably, considerable commonality of aims do exist between them. Burns et al (2003) distilled the aims of these terms into five broad personal responses to science, which may be grouped under the label AEIOU (the vowel analogy): Awareness of science;. 11.
(16) Enjoyment or other affective responses to science; Interest in science; the forming of science-related Opinions; and Understanding of science. These five aims provided a sharing goal with science communication and science education, giving us the foundation for further research and evaluation. It is a suitable framework to develop research tools in this study to investigate the different effects between daily science communication and educational science communication. Therefore, we revised the definition to fit in our study based on Burns’s definition: (1) Awareness: Being aware of the development of science and scientific methodology, and having positive attitudes toward science. (2) Enjoyment: The current modern, convenience and developed technology that as a result brings forth an enjoyable life experience and appreciates it. (3) Interest: A desire that tends to dig or pay attention to more about scientific issues or activities. (4) Opinion formation: A science-related concept formed in the public’s reflection to support their own opinions. (5) Understanding: A comprehension of scientific concepts gained. Overviewing the whole picture, it would seem obvious that science education and science communication have a fair amount of overlap. Both of these two fields bring certain ways of viewing the world and values about what is important to study. Therfore, Davis & Russ (2015) suggested that it is time for these two fields to start sharing perspectives, methods, and theories that can holistically enrich each other, as well as help society by empowering people to critically engage with science.. 12.
(17) 2-2 Broadcast TV News to Bridge Science Education and Science Communication Science news is an important kind of media for the general public’s understanding of scientific innovations or controversial scientific issues. For people graduated from school school, science news becomes a crucial tunnel keeping the general public stay updated with recent scientific activities in contemporary society (Huang & Chien, 2004). Furthermore, Southwell and Torres (2006) suggested that TV news help the audience to understand science and promotes discussion of scientific issues. However, the function of communication media is not only to deliver scientific information, but also to shape scientific information (Dimopoulos & Koulaidis, 2002). In other words, communication media provides us not only with news about science but it actually guides the viewer to understand and pay attention to science. Therefore, the quality, vision and perspective of science communication may indirectly decide people’s opinions and action when they face social scientific issues. In order to give us a whole picture of science in social issues from multiple views, Wu et al. (2015) proposed the “Different Science News” program with the aim of combining the TV news media and science education. Sharing what science education cares most about is to carefully curate scientific and instructional content for the public’s understanding with TV news media, which is good at exposing stories vividly in order to motivate audiences to watch. The following section will introduce what aspect of education and communication’s elements were considered during the production.. 2-2-1 Cognitive Loading Theory – 90 s in Length – Well Structured Content According to congnitive load theory (Sweller, 1994), the audience may lose attention due to the limited attention span of humans. According to Figure 2, when one perceives and continues to receive information through sensory memory (e.g., to read, listen, or watch), these little pieces of information require “mental effort” to become “retainable.” These pieces are then temporarily. 13.
(18) stored in the working memory, waiting to be further “compiled.” If these pieces become meaningful, they may enter the long-term memory (Sweller, Chandler, Tierney, & Cooper, 1990). Thus, if too much or overly extraneous information, is placed in the short 90-second video, it would compete with the actual desired content of the scientific subject (i.e., it would compete for limited capacity of human working memory).. Based on this theory, Sweller (1994) argued that a well structured instructional design can be used to reduce the cognitive load in learners. Thus, Wu et al. (2015) structured the following components into each video: (1) the main ideas to be addressed (e.g., scientific misconceptions in daily lives, current scientific developments or inventions, social scientific issues, etc.); (2) scientists, to explain the topics and facts, or to demonstrate the research with scenes of performing actual experiments; (3) connections from the story to our daily lives; (4) animations, to convey procedure or to enhance the understanding of more complex scientific concepts.. Figure 2 The illustration of cognitive loading theory (address from Cooper, 1998).. 14.
(19) 2-2-2 Multimedia – Computer Simulation/Animation – Learn Complex Scientific Concepts. In each episode of news (Wu et al., 2015), there was an animation section of about 20 seconds explaning main scientific concept. The animations were designed by the principle of multimedia learning. Mayer (2009) showed that people learn more deeply from words and graphics than from words alone. The multimedia principle forms the basis for using multimedia instruction, that is, instructions containing words (such as spoken text or printed text) and graphics (such as illustrations, charts, photos, animation, or video) that is intended to foster learning. Unlike general science news which convey incomplete or even inaccurate scientific concepts, “Different Science News” program (Wu et al., 2015) is devoted to produce Educational Science News which has complete, specific, and accurate scientific concepts in order to promote learning science in daily life. Therfore, the principles of multimedia learning they used are summarized in the points that follow.. For reducing extraneous processing, four principles were used to reduce elements not related to instructional goal: (1) Coherence principle: People learn more deeply when extraneous words, pictures, or sounds are excluded rather than included (Mayer, Heiser& Lonn, 2001). (2) Signaling principle: People learn more deeply when cues are added that highlight the main ideas and the organization of the words (Mautone & Mayer, 2001). (3) Redundancy principle: People learn more deeply from animation and narration than from animation, narration, and on on-screen text (Moreno and Mayer, 2002). (4) Spatial contiguity principle: People learn more deeply when corresponding words and pictures are presented nearer rather than further from each other on the page or screen (Moreno and Mayer, 1999).. For managing essential processing, two principles were used with the aim of representing essential material:. 15.
(20) (1) Pre-training principle: People learn more deeply from a narrated animation when they have had training in the names and characteristics of the main concepts (Mayer, Mathias & Wetzell, 2002). (2) Modality principle: People learn more deeply from graphics and narration than from graphics and on-screen text (Moreno and Mayer, 1999).. For fostering generative processing, one principle was used with the aim of making sense of essential material: (1) Voice principle: People learn more deeply when the narration is spoken in a standard-accented human voice than a machine voice (Mayer, Sobko, and Mautone, 2003).. 2-2-3 News Values – Domestic Science Development – Promotion of PUS. News values, sometimes called news criteria, determine how much prominence a news story is given by a media outlet, and the attention it is given by the audience. Galtung and Ruge (1965) analyzed international news stories to find out what factors they had in common and what factors placed them at the top of the news agenda worldwide. In their study, they put forward a system of 12 factors - a kind of scoring system - a story which scores highly on each value is certain to come at the start of a TV news bulletin, or make the front page of a newspaper. One of these 12 news values factors is proximity, which is to do with people or places close to home. Stories which happen closer to the viewer has more significance to the viewer. Note that proximity does not have to mean geographical distance. Stories from countries with which the viewer has a particular bond or similarity have the same effect.. In the production of news (Wu et al., 2015), although it spents a lot of time running local interviews and compiling stories from local science institutes, it’s essential to achieve the requirements of news values and then made audience pay more attention. The public’s understanding of science and its development was directly affected by the public’s long-held social, religious, and cultural beliefs. Take for example the controversial research area of stem cells;. 16.
(21) its research direction may vary from country to country because of cultural or religious beliefs. Thus, learning about the scientific research differences among various cultures and societies is one of the goals within the promotion of the public understanding. Therefore, it is of important to make the audience pay attention to domestic science news firstly, which will allow them to distinguish differences or appreciate new ideas from each other.. 2-2-4 Framing – Journalist vs Scientist – Sharing Specialty Goffman (1974) described a frame as “a set of simple elements that organize the perception of a given situation and how those elements tune the interpretation of a phenomenon”. In communications research, it typically focuses on either the creation of frames, referred to as frame building, or the effects of those frames, referred to as frame setting (Tewksbury & Scheufele, 2009). Frame building research often studies the types of frames contained in discourse surrounding controversial or pioneering scientific research, and how sources and journalists negotiate these frames to create interpretive storylines (Nisbet, Brossard, & Kroepsch, 2003; Nisbet, 2009).. The central group members in the production consisted of science educators and journalists, both of which strove to help people understand what science is. However, a great gap existed in terms of different frames viewing each scientific topic, which caused a tug-of-war when working on. Therefore, there were a lot of negotiations (e.g., frame building) from searching scientific topics to video postproduction. Though the collaboration is a tug-of-war, the idealization of sharing specialties between science communication and science education was gradually realized throughout the path of collaboration. On one side, journalists were learning a new perspective on how delivering the “how science is made” aspect when scientific concepts got a little bit deeper. At the same time, science educators were learning how the local public may be better motivated, educated, and engaged through broadcasted TV news.. 17.
(22) Chapter3 Methodology 3-1 Research Framework The aim of this study is to explore participants’ AEIOU responses under Daily Science Communication (DSC) and Educational Science Communication (ESC). According to the purpose of this study, we designed a research framework stated in Figure3, including the independent variable (i.e., DSC/ESC), the dependent variable (i.e., AEIOU responses) and the control variable (i.e., SLiM assessment).. Figure 3 Research framework of exploring participants’ AEIOU responses to science.. 18.
(23) 3-2 Participants and its background information In this study we chose two classes of students (N=121) taking a general education course as participants. To maintain consistent results that participants would produce AEIOU responses to science between the two classes, participants must have similar backgrounds to science training, science interest, and must have grown up in similar environments of science education and science communication. Because the video was news from the media of TV, the usage frequency of different kinds of media should be of concern. Therefore, the information of backgrounds included six classifications.. First of all is SLiM test, a new research tool for accessing scientific literacy which combines the views of the science experts and the media (Rundgren et al., 2010). It contained 50 of the most common contemporary scientific concepts presented both in Taiwanese news media and textbooks. To an extent, SLiM can reflect to what extent people are soaked into the daily science communication and receive the scientific concepts about society. According to the research framework the SLiM assessment is the most important objective control variable in this study. In the following research, SLiM will be divided into two groups - Higher SLiM (HS) and Lower SLiM (LS) according to participants’ SLiM test scores.. In order to divide participants into HS and LS groups, we chose the median as our division boundary. The median is a statistical measure of central tendency, that is, a measure of where the middle of a set of number is. More specifically, the median is the number that splits the numbers into two sets, one higher and one lower (e.g., numbers that are unusual). This is an advantage (Petrie & Sabin, 2009) because we do not want a person whose SLiM achievement especially high or low to have as much influence as others. According to the descriptive statistics of SLiM (Table 1) the median SLiM score is 39 and thus divided the scores into two groups; one above 39 as the Higher SLiM (HS) group and one under 39 as the Lower SLiM (LS) group. The results in this study would present on the ground of these two controlled conditions.. 19.
(24) The other five classifications are pre_sci (i.e., if participant was trained under scientific expertise oriented courses before university), grade, gender, the type and frequency of media usage (e.g., newspaper, TV, and internet), and interested scientific fields (e.g., agriculture, exploration, technology, earth, environment, DIY, nature, psychology, and energy). After running the homogeneity of variances as shown in Table 2, we can see that each background variables is not significant (i.e., p>.05), but that participants from the two groups shared homogeneous characteristics. Table 1 Descriptive statistics of SLiM Items. Statistic. Std. Error. Mean. 36.4628. .64614. 5% Trimmed Mean 36.9766 Median. 39.0000. Variance. 50.517. Std. Deviation. 7.10756. Minimum. 14.00. Maximum. 47.00. 20.
(25) Table 2 Test of Homogeneity of Variances (N=121) SLiM test pre_scia gradeb genderc newspaperd TVd internetd arigriculturee exploratione technologye earthe environmente DIYe naturee psychologye energye. Levene Statistic. df1. df2. Sig.. .754 3.280 .450 5.068 .047 .849 .000 .118 1.730 .000 1.244 .459 .449 .017 .066 .061. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1. 119 119 119 119 119 119 119 119 119 119 119 119 119 119 119 119. .377 .073 .504 .057 .830 .359 .994 .732 .191 .993 .267 .499 .504 .896 .797 .805. a. Pre_sci: 0 = non pre_sci, 1 = pre_sci. bGrade: 1 = freshmen, 2 = sophomore, 3 = junior, 4 = senior. c Gender: 1 = male, 2 = female. dNewspaper, TV, and Internet: 1 = less then 1 day per week, 2 = 1-3 days per week, 3 = 4-6 days per week, 4 = everyday. eAgriculture, exploration, technology, etc.: 1 = very not interested in, 2 = not interested in, 3 = interested in, 4 = very interested in.. 21.
(26) 3-3 Research Procedure Firstly, we developed a testing version of instrument to explore AEIOU. The procedure of developing this version was composed of questions designed (including the questions of individual background information), experts review, modify and delete questions with experts’ comments (Figure 4). Then we invited participants taking the same general education course from the two classes and divided them into two groups, one of which was the DSC group, and the other as the ESC group. On average, students had to finish the questionnaire in 40 minutes. This study was successfully completed on April, 2015. Figure 5 represents the summary of research procedure.. Figure 4. The procedure of instrument development.. 22.
(27) Figure 5. The summary of research procedure.. 23.
(28) 3-4 AEIOU Instrument Development. 3-4-1 Questions Design. 3-4-1-1 Type of Question To explore the different outcomes of AEIOU between participants in the DSC and ESC groups properly, we developed a questionnaire which included three types of questions (Table 3). Firstly, a five-point Likert scale was used to measure AEI dimensions. The scoring of AEI was from 1 point (completely disagree) to 5 point (completely agree) with a higher total score designating higher levels of AEI. Secondly, open ended questions were used to measure the O dimension in order to make participants freely express their own opinions. And the last part of the questionnaire was for U dimension, which were true-or-false type questions and semi-opened-ended questions. In each question participants were required to write down the reasons only when they chose to disagree with the statements to ensure they truly understand science. It is worthwhile to mention the scoring of Understanding dimension. If participants answered right in true-or-false question but the reason was scientifically wrong, then we would still count this as wrong answer and participants would lose 1 point (Appendix 3).. Table 3 Three types of questions in AEIOU questionnaire.. Dimension. AEI. O. U. Question type. Five-point Likert scale. Open-ended. True and False Semi-opened-ended. 24.
(29) 3-4-1-2 Content of Questions The questions of AE dimensions were adopted from a previously developed tool, which was a measurement to evaluate civic scientific literacy (Huang, 2012), and were revised for the purpose of this study. In our initial version of instrument (Tabl3 6), there were ten and eight questions for the measuring of the A and E dimension respectively, and as for the IOU dimensions, we designed five, three, and four questions respectively based on the purpose of study by ourselves. The sample items of each dimensions are presented in Appendix 1. 3-4-2 Validity The content validity was established by expert judgment. In order to certify the usefulness of questions in A, E, I, O, and U, we solicited the opinions of experts, which were two from science communication and one from science education. The questions were revised and useless items were deleted, which were question 6 in Awareness, question 7 in Enjoyment, and question 1 in Interest according to the experts’ comments before the study began. 27 questions remained in the testing version of questionnaire (Table 6).. 3-5 Factor Analysis of A, E, and I In order to determine the factor structure (i.e., A, E, and I) in questionnaire, we used SPSS 21 to run an exploratory factor analysis (EFA). Based on Hair et al. (2006), a factor loading above 0.6 is enough for a construct, which means any factor loading below 0.6 should be deleted. After analyzing, the structure was consistent with our original three dimensional setting of A, E, and I, (Table 4). The questions 1, 7, 8, 9, 10 were for the “Awareness” aspect; questions 3, 4, 5 for the “Enjoyment” aspect; and questions 2, 3, 4, 5 were for the “Interest” aspect. As a result, we gained analysis version of instrument (Table 6), which remained 19 questions including 5 for Awareness, 3 for Enjoyment, 4 for Interest, 3 for Opinion, and 4 for Understanding.. 25.
(30) Table 4 Factor loadings and Cronbach’s alpha values for the three factors Item Factor 1 : Awareness (A) A 01 A 02 A 03 A 04 A 05 A 07 A 08 A 09 A 10 Factor 2 : Enjoyment (E) E 01 E 02. Factor 1. Factor 2. .636. .740 .811 .713 .800. E 03 E 04 E 05 E 06 E 08 Factor 3 : Interest (I) I 02 I 03 I 04 I 05 Eigenvalues % of Variance Cronbach's alpha (α). Factor 3. .772 .780 .796. .865 .872 .800 .761 3.263 16.313 .837. 1.864 9.321 .766. 26. 5.701 28.503 .865.
(31) 3-6 Reliability in A, E, I, and U In order to ensure the inter-rater reliability, we utilized the analysis of Cronbach’s alpha (Cronbach, 1951). A commonly accepted rule for describing and judging the standard of internal consistency using Cronbach’s alpha is illustrated in Table 5 (Nunnally, 1978). After the analysis of Crobach’s alpha (by SPSS 21), the inter-rater reliability was 0.837 in A, 0.766 in E, 0.865 in I (Table 4), and 0.610 in U. According to Table 5, the internal consistency of AEI were good and U was acceptable. As a result, AEIU has substantial agreement.. Table 6 shows an entire view of evolution of the AEIOU instrument’s number of items through the study. The next section will introduce the methods we analyzed and data which was collected from the final version that is the analysis version of instrument. Table 5 Cronbach’s alpha standard of internal consistency Cronbach's alpha. Internal consistency. α ≥ 0.9 0.7 ≤ α < 0.9 0.6 ≤ α < 0.7 0.5 ≤ α < 0.6 α < 0.5. Excellent (High-Stakes testing) Good (Low-Stakes testing) Acceptable Poor Unacceptable. Table 6 The evolution of instrument’s numbers of items in each dimension through the study. Dimension. Initial version. Testing version. A E I O U. 10 8 5 3 4. 9 7 4 3 4. Total. 30. Expert review. 27. 27. Analysis version 1.Factor analysis 2.Reliability X 1.Reliability. 5 3 4 3 4 19.
(32) 3-7 Data Analysis In this section, we will elaborate the methods that will be used in analyzing the data we collected from Analysis version of the instrument. There were three classifications of analysis methods in this study. The first one is the simple linear regression model to test the prediction of SLiM assessment toward AEIU responses. The second one is the independent samples t test model to test the difference on the AEIU responses between DSC and ESC group. The last one is the coding analysis model which looks for different opinion formations between participants in DSC and ESC. Each of the models are explained in more detail in the following sections. 3-7-1 Simple Linear Regression In the simple linear regression model, we predict scores on one variable from the scores of a second variable. The variable we are predicting is called the criterion variable and is referred to as AEIU responses in this study. The variable we are basing our predictions on is called the predictor variable and is referred to as SLiM assessment in this study. In simple linear regression, the topic of this section, the predictions of AEIU responses when plotted as a function of SLiM to form a straight line. Therefore, if a straight line existed, it can predict the change that SLiM assessment results will bring to AEIU responses. 3-7-2 Independent Samples t Test The Independent Samples t Test compares the means of two independent groups in order to determine whether there is statistical evidence that the associated population means are significantly different from each other. The variables used in this study are known as the independent variables (i.e., A, E, I, and U) and dependent variable (i.e., DSC and ESC). Significance levels adopted in this study are at .05 or .01 level which is commonly used in educational research. All analysis was conducted by SPSS Version 21.0. The results of above analysis will be listed in the chapter 4.. 28.
(33) 3-7-3 Coding Analysis The question style of Opinion was open-ended. The data we collected from participants was in the form of texts. At this first level of coding, we looked for distinct concepts and categories in the data, which will form the basic units of analysis. In other words, we were breaking down the data into first level concepts, and second level categories. Then, we used the concepts and categories while re-reading the text to confirm that our concepts and categories accurately represented in the participants’ responses. After transferring the final concepts and categories into a data table, we would submit our table to expert for inter-rater reliability.. 29.
(34) Chapter4 Results 4-1 Simple Linear Regression Results of SLiM A simple linear regression was calculated to predict AEIU responses based on the SLiM assessment results. Table 7 shows that SLiM assessment results were significantly predicted AEIU (A: F (1, 119) = 16.869, p < .01; E: F (1, 119) = 7.689, p < .01; I: F (1, 119) = 5.487, p < .05; U: F (1,119) = 7.345, p < .01) by the following formula: A = 15.564 + 0.378 x SLiM, E = 8.750 + 0.246 x SLiM, I = 9.167 + 0.210 x SLiM, U = 34.169 + 0.241 x SLiM. As a result, SLiM assessment can predict participants’ AEIU responses in this study. The results of data analysis in this study showed the same trend that participants with higher SLiM scores have higher AEIU scores. Table 7 Summery of linear regression for SLiM assessment results. Model Variables. Beta. R2. 1. A. .378. .143**. 2. E. .246. .061**. 3. I. .210. .044*. 4. U. .241. .058**. *. Significant at the 0.05 level **. Significant at the 0.01 level. 4-2 Independent Samples t Test Results of AEIU HS participants’ U responses (N=69) has a statistically significant difference between DSC (M = 1.51, SD = 1.22) and ESC group (M = 2.06, SD = 1.01), t (67) = -2.01, p ≤ .05 (Table 9). Furthermore, LS participants’ I responses (N=52) also had a statistically significant difference between DSC (M = 10.95, SD = 2.89) and ESC group (M = 12.47, SD = 2.42), t(50) = -2.053, p ≤ .05 (Table 10).. As for the rest of results, such as all participants’ AEIU responses (N = 121) (Table 8), HS. 30.
(35) participants’ AEI responses (N=69) (Table 9), and LS participants’ AEU responses (N=52) (Table 10), there were no statistically significant difference between DSC and ESC group. Therefore, we fail to reject the null hypothesis that there is no difference in AEIU responses between DSC and ESC. Table 8 All participants’ comparison of AEIU responses.. A. E. I. U. Group. N. Scores. Mean. SD. t. p. DSC. 57. 25. 20.91. 3.08. --. --. ESC. 64. 25. 21.06. 2.54. --. --. Total. 121. 25. 20.99. 2.81. -.294. .769. DSC. 57. 15. 11.33. 1.87. --. --. ESC. 64. 15. 10.91. 1.85. --. --. Total. 121. 15. 11.12. 1.86. 1.260. .210. DSC. 57. 20. 12.05. 3.23. --. --. ESC. 64. 20. 12.81. 2.86. --. --. Total. 121. 20. 12.43. 3.05. -1.372. .173. DSC. 57. 4. 1.51. 1.20. --. --. ESC. 64. 4. 1.58. 1.12. --. --. Total. 121. 4. 1.53. 1.16. -.330. .743. 31.
(36) Table 9 High SLiM participants’ comparison of AEIU responses.. A. E. I. U. Group. N. Scores. Mean. SD. t. p. DSC. 35. 25. 21.80. 2.76. --. --. ESC. 34. 25. 21.59. 2.16. --. --. Total. 69. 25. 21.70. 2.46. -.354. .725. DSC. 35. 15. 11.77. 1.59. --. --. ESC. 34. 15. 11.29. 2.01. --. --. Total. 69. 15. 11.53. 2.00. 1.096. .277. DSC. 35. 20. 12.74. 3.28. --. --. ESC. 34. 20. 13.12. 3.21. --. --. Total. 69. 20. 12.93. 3.25. -.479. .633. DSC. 35. 4. 1.51. 1.22. --. --. ESC. 34. 4. 2.06. 1.01. --. --. Total. 69. 4. 1.79. 0.25. -2.01. .048. 32.
(37) Table 10 Low SLiM participants’ comparison of AEIU responses.. A. E. I. U. Group. N. Scores. Mean. SD. t. p. DSC. 22. 25. 19.50. 3.10. --. --. ESC. 30. 25. 20.47. 2.83. --. --. Total. 52. 25. 19.99. 2.97. -1.170. .247. DSC. 22. 15. 10.64. 2.11. --. --. ESC. 30. 15. 10.47. 1.57. --. --. Total. 52. 15. 10.56. 1.84. .333. .740. DSC. 22. 20. 10.95. 2.89. --. --. ESC. 30. 20. 12.47. 2.42. --. --. Total. 52. 20. 11.71. 2.66. -2.053. .045. DSC. 22. 4. 1.50. 1.19. --. --. ESC. 30. 4. 1.03. 1.00. --. --. Total. 52. 4. 1.27. 1.10. 1.54. .130. 33.
(38) 4-3 Coding Analysis of Opinion Formation Firstly, we calculated the totality of concepts mentioned by participants and divided it by the population of participants. We gained the change of opinions formed (per person) in each question. In the ESC group, participants gained more concepts in each question, especially LS participants (see Table 11). Secondly, we found there were two categories in each of the three questions. An overview of those categories showed that there are only two types of concepts in their opinions namely a common concept and a scientific concept. Driver, Asoko, Leach, Mortimer and Scott (1994) illustrated the meaning of “common concept” as a range of knowledge schemes that are drawn on to interpret the phenomena people encounter in their daily lives. These are strongly supported by “personal” experiences. On the contrary, they portrayed scientific concepts as the public knowledge that is “constructed” and communicated through culture and social institutions of science because organizing concepts and practices of science are unlikely to be discovered by individuals through their own observations of the natural world.. As a result, we integrated our discovery about two types of concepts into the result of coding analysis, and created coding scheme (Table 12). Generally speaking, scientific concept is the majority type of concepts in each of the three questions. Furthermore, the proportion of scientific concept is even higher in ESC group then in DSC group from both HS and LS participants. To illustrate this point, we will present each question’s percentage of two categories specifically from participants’ opinions in the following three sections (Examples see in Appendix 4).. 34.
(39) Table 11 Opinions formation per person DSC/ESC. All. HS. LS. Q1 Q2 Q3. 1.5/1.9 0.9/1.2 1.2/1.5. 1.5/1.7 0.9/0.8 1.2/1.2. 1.5/2.1 0.9/1.7 1.3/1.9. Table 12 Opinions coding scheme Type. Categories. Concepts. Scientific concept. Natural environment. 1 Basin, 2 Earthquake, 3 Sea level, 4 Volcano, 5 Torrential rain, 6 Climate, 7 Lake, 7 Soft soil, 8 Plate, 9 Typhoon, 10 Geography, 11 Seismic wave, 12 Sault water intrusion, 13 Debris flow disaster, 14 Clammy weather, 15 Geology, 16 Soil liquefaction, 17 Fault, 18 Tsunami.. Seismological-relate d knowledge. 1 Anti seismic construction, 2 Building structure, 3 Frequency, 4 Stable foundation, 5 Stratum, 6 Seismic wave, 7 Resonance effect. 1 Green house effect, 2 Climate anomaly, 3 Global warming, 4 Ecological unbalanced, 5 Pollution, 6 Ocean acidification, 7 Sea level, 8 Ocean warming, 9 Acid rain.. Natural alteration. Common concept. Manmade consequences. 1 Defective drainage, 2 High-rising buildings, 3 Nuclear power plant, 4 Population density, 5 Soil and water conservation, 6 Human activities, 7 Industrial pollution, 8 Over-development, 9 Anti-seismic construction, 10 Probability, 11 Urban heat island, 12 Developed city.. Personal safety. 1 Age of building, 2 Geography, 3 Escape, 4 Disaster prevention, 5 Feeling of vibration.. Living essential. 1. Breathe, 2 Technology, 3 Photosynthesis.. 35.
(40) 4-3-1 Q1 “In your opinion, please describe Taipei City’s living conditions and environment”. After coding analysis, we found two categories. The “Manmade Consequences” category, referring to the discomfort in the living environment caused by human activities, and the “Natural Environment” category, referring to the original geography, geology, or climate naturally shaped a risky living environment around Taipei city. According to Figure 6, most participants tend to form opinions in the “Natural environment” perspective whether in DSC or ESC group. For HS participants, the ratio of two categories remained almost the same and dominated by the category of “Natural environment” whether in DSC or ESC group. For LS participants, the category of “Natural environment” increased to an extent in ESC group and its percentage almost approached HS participants’ in ESC group.. Figure 6 Q1’s percentage of categories from HS and LS participants. 36.
(41) 4-3-2 Q2 “When an earthquake hits, is a taller building or a shorter building safer? Describe your opinion.”. After coding analysis, we found two categories. “Personal safety” referring to survival being the first thing that comes to mind in an earthquake and “Seismological-related knowledge”, which involves professional knowledge, especially in a seismic region in this study, which had to be learned. According to Figure 7, the category of “Personal safety” took the lead in general group. For HS participants, it took almost half of percentage. For LS participants, it even surpassed half of percentage.. However,. both. HS. and. LS. participants. gained. more. concepts. about. seismological-related knowledge in ESC group. Especially LS participants grew much more seismological-related knowledge then HS participants and even surpassed its percentage.. Figure 7 Q2’s percentage of categories from HS and LS participants. 37.
(42) 4-3-3 Q3 “In your opinion, how might carbon dioxide affect our living environment?”. Two categories were found after coding analysis. “Living essential”, referring to the essential condition to maintain peoples’ living, and “Natural alteration”, referring to manmade consequences. A series of oceanic, ecological, and climatological change around the world were mentioned by participants in this category. According to Figure 8, most participants tend to form opinions in “Natural alteration” perspective whether in DSC or ESC group. For HS participants, the ratio of two categories remained almost the same and predominated by the category of “Natural alteration” whether in DSC or ESC group. For LS participants, the category of “Natural alteration” increased to an extent in ESC group and its percentage even slightly exceeded HS participants’ in ESC group.. Figure 8 Q3’s percentage of categories from HS and LS participants. 38.
(43) Chapter5 Discussion After analyzing the data, we found IOU dimensions have been promoted by Educational Science News within LS participants, all participants, and HS participants respectively. However, there were no differences AE dimensions between the DSC and ESC groups within participants. We will discuss our findings in five parts- Awareness, Enjoyment, Interest, Opinion-formation, and Understanding.. 5-1 Awareness There was not any difference in the awareness dimension in between the DSC and ESC groups. This shows that Educational Science News fail to improve participants’ awareness to science in this study. The reason might be related to the fact that Science news have been neglected by Taiwan’s media for a long time (Hsieh, 1992). When people are out of school, science news was the easiest way for the public to receive science information (Huang & Chien, 2004). From the previous research, we can easily find out that science news has been vulnerable groups in the Taiwan’s media for a long time. According to the Lin’s statistic study (2009), Taiwan's science news only accounted for less than 0.2 percent in the overall amount of news. Furthermore, even if science news had been reported out, most of science news was always dramatized by media in order to attract audience. Some researchers have pointed out that science news tend to focus on scientists’ individual background regardless of their science achievement, and emphasize the social scientific issues on reporting out controversial opinions and not on the scientific facts (Huang & Chien, 2010; MacDonald, 2005; Priest, 2001; Hsieh, 1992). This may distract the public’s attention from real substance that is scientific view of issues (Hsieh, 1992). Therefore, the public has exposed to an environment for a long time in which the media’s coverage about science was low and usually off the scientific content. It has led them to a low awareness of science and therefore show difficulty in discovering the real substance of science hidden behind. 39.
(44) social issues. It is obvious that raising the public awareness of science is not able achievable in a short period of time.. 5-2 Enjoyment The enjoyment dimension in this study is to ask participants to what extent current modern, convenience and developed technology brings forth a more enjoyable life experience. The results showed that there is no difference between the DSC and ESC groups. This might be because of the public’s general science content preference. Bucchi, M. (1998) said it is easier for people to pay attention to the issues which are related to personal life environment, diet, health, survive and so on. The public’s preference to science content is usually related to daily life experience. However, some contents of Educational Science News in this study included progressive developmental ideas, large-scale (e.g., not personal) influence regions, or complicated high-end technology, such as alternative energy, global climate change, and volcano detection. The media rarely reports on these matters and therefore it is difficult for the public to contact these topics in daily life and thus make participants feel that science is not close to them which leads to no significant difference of the public’s enjoyment of science.. Even the fact showed participants haven’t generally accepted topics like these, in order to promote the public’s science literacy the media cannot always report a single kind of scientific topic based on Receiver Oriented Model (Kuan, 2010). This model does not allow the public to know the whole picture in terms of science (Huang & Chien, 2006). The breaking point to solve progressive developmental ideas, large-scale (e.g., not personal) influence regions, or complicated high-end technology science contents, which the public hardly accepted in general, may lie in how to narrate its contents and packaging into a good story.. MacIntyre (1981) once said that human beings are naturally a story telling animal. He thought that story telling is a tool that prevails through our daily life and a well-grounded, basic form within. 40.
(45) our communication. We are not only story receivers but also story creators (Berger & Luckman, 1966). Tsai (2004) pointed out that a good story is an important basis for interaction, identification, and reliance between humans and enables them to enhance personal or community cohesion to achieve the possibility of convincing each other of ideas. On the other hand, if scientific knowledge can be communicated through good story marketing, it is possible to make it spread out. Lin (2000) considered that the key point in persuading the audience is usually not by the consistency of communication contents itself but by the connection of a story and daily lif. Instead of completely explaining a hard scientific knowledge, if a story can be identical to general human nature and has a meaningful value system, it will promote human’s affection interaction, have the possibility to persuade audience. Fisher, 1989. , and eventually communicate positive values of science. development to them. Science communication should progress in this direction with efforts in the future.. 5-3 Interest LS participants showed more interest to science in the ESC group. Lee (2014) once said that an effective collaboration of scientists and media can guide audience to produce an interest for science. However, it’s difficult to build an effective collaboration because scientists do not talk enough about science knowledge through popular language. At the same time, most of media producers majored in literature-related subjects and thus lack science literacy (Han, 1990) and therefore it is difficult for media producers to understand the explanation from scientists. Therefore, there are many conflicts during their conversations and thus collaboration can be difficult or even turn into the hostile relations, just like oil and water can’t mingle together (McCall, 1988). Because of the abovementioned situation, the content of science communication becomes too complicated that the public stays away from it or the information portrayed is too inaccurate that the public has a distrust in science information in the media. There were no benefits to improve science interest. The reason why there is such difficulty in collaboration is because of Shunt Education in Taiwan is too early.. 41.
(46) Most of people were asked to determine studying in either science or literature group during senior high school, and from that time learning different materials. Especially when people get into the university, they gradually shaped their own professional skill, building up their own academic community, and eventually cannot have a disciplinary conversation with other profession (Mo, 2014). Considering the issues of the education system is a big enterprise and will not be changed soon. As a result, a possible way to maintain science communication’s function of evoking science interest is to input a communicator between scientists and media producers. Mo (2014) said transforming science knowledge is the element of successful science communication, which including “What to say” and “How to say”. No doubt, “How to say” is mainly the task of media producers. Therefore, the role of communicator is mainly to help scientists effectively transform science knowledge, and communicate “What to say” to media producers with the transformed knowledge through popular language. In “Different Science News” program, science educators played the role of sufficient communicators. Transforming science knowledge is the greatest strength of science educator. In this case, media producers are learners, and scientists are source of teaching materials. After transforming science knowledge form scientists, science educators communicated science through popular language to media producers just like an instructor would educate a learner. With the science educator, media producers may understand science better, have more ideas to discuss with scientists, and eventually bring “What to say” and “How to say” into full play. Therefore, the more conversation take place between the media and scientists, the more effective science communication can be to evoke the audience’s science interest. According to our results, the production of educational science news seems to make participants produce more science interest, which means this pattern of tripartite collaboration – scientists, science educator, and media is a worthwhile collaboration to keep developing. In the end, the reason that HS participants showed no significant “Interest” difference between DSC and ESC might arise from the high science. 42.
(47) preference they already have. Generally, people who prefer science have more motivation and would like to pay more efforts to learn about science (Rundgren et al., 2010). Therefore, the effect of promoting science interest is relatively limited for HS participants.. 5-4 Opinion Formation In ESC group, both HS and LS participants’ scientific concepts were much more than the DSC group, as shown in Table 13. Their answers included much more scientific concepts to support opinions in average. It showed that Educational Science News (ESN) can effectively deliver some specific scientific concepts. Based on Wu’s study (2015), ESN is a well-structured video including specific scientific concepts during 90sec in each section making it easy for them to receive new concepts. Under this design idea, ESN intrinsically helps the public to gain multiple opinions. In the future, when facing scientific issues, they can have their own opinions to engage in discussion. This is a sharing goal of science communication and science education (Kolstø, 2000). Table 13 The proportion of scientific concepts generated by participants. DSC/ESC (%). HS. LS. Q1 Q2 Q3. 83/86 53/77 95/90. 66/83 17/81 79/91. 5-5 Understanding HS participants showed a better ability to understand science knowledge in ESC group. There were four questions related to the four scientific concepts of the video, which were explained in a way of computer animation, including seismic amplification, dormant volcano, anti-seismic construction, and ocean acidification. With the help of animation during the video, participants might gain scientific knowledge. Because science related issues are usually complex and abstract, it can be explained clearer by means of flowcharts or schematics. Some studies (Hinnant & Len-Ríos, 2009) also found that journalists generally agreed with the fact that the audience is visually-oriented.. 43.
(48) Therefore, the application of animation or illustrations can effectively improve audience’s understanding of science issues. Furthermore, the animation was designed to follow the principle of Mayer’s multimedia learning theory in this study. It is reasonable to claim that participants should be able to learn some scientific knowledge from Educational Science News, and lead to understand of science. However, the results showed only HS participants have significantly improved in ESC group, LS participants’ understanding of science just had a slight improvement in ESC group.. The reason might come from the original background of science knowledge that can be seen as prior knowledge about science. Sanchez (2009) said that many instructors misunderstood that visualization can directly cause the improvement of understanding. In fact, the learner’s prior knowledge will affect the individual’s thinking and interpretation, and eventually interfere with the understanding and memory of the individual (Kendeou & van de Broek, 2005). Therefore, we cannot directly claim that animation is the only reason helping participants to understand science, but rather also have to consider participants’ prior knowledge to explain the improvement in ESC group. Cook, Wiebe, & Carter (2008) found that individual who is sufficient with prior knowledge about the topic tend to spend more time focusing on the conceptual features of the graphic related to the topic, and build up their understanding about this topic. On the contrary, individual who lacks prior knowledge can only see the superficial features of the graphic, connecting this features to the topic, resulting in a situation that they are unable to understand the basis of the topic. For HS participants in this study, they already have more sufficient prior knowledge about science then LS participants, and might have more ability to connect graphics to scientific concepts during animation, thus leading them to a better understanding of science. This might be one of the reason why HS participants showed significant improvement on understanding of science.. 44.
(49) Chapter6 Conclusion & Future Research 6-1 Conclusion From the study, we gained a preliminary outcome of what Educational Science News (ESN) promotes. No matter participants in what extent of Scientific Literacy in Media (SLiM), they benefited from ESN that is “Interest” for LS participants, “Opinion-formation” for all participants, and “Understanding” for HS participants. It means that ESN is suitable for wide range of public in society to cultivate science literacy. It has potential to make up the present deficiencies in Taiwan’s media. On the other hand, maintaining public’s literal function of AEI to science can’t only rely on teacher’s cultivation during school, but also need an effective science communication environment after school for life long. As a result, AEI have never been easy to change by just contacting ESN once and will take time because they have been affected by the media for a long time. However, in our study, “Interest” did get promoted by it.. These unneglectable effects strongly affirm the feasibility of cooperation among science educators and the media. It shows a promising future can be created, if ESN keeps developing over a long term within Taiwan’s media and becomes a model for science news production. There will be an effective science communication environment where the public not only learn (AU) about and appreciate (E) science but are also willing to engage (IO) in science.. 6-2 Future Research The framework of research tool in this study was based on the definition of science communication (Burns, 2003)- AEIOU. The questions of OU aspects in our questionnaire were closely related to the content of Educational Science News, but were confirmed by experts that the questions were able to be answered by the public in general. Therefore, if researchers want to develop a questionnaire in a common use independent of science contents, the questions of OU. 45.
(50) need to be of questions that truly represent the public’s OU in general. Besides, the participants in this study only included 18-25 years old young people which means there could be different outcomes if a different age group was used.. 46.
相關文件
「倍思科學」教育系統,是由國內長期推動科學教育的專家學者和優秀的中小學教師共同規
配合小學數學科課程的推行,與參與的學校 協作研究及發展 推動 STEM
• 第三種教學觀認為,教學的目的是改變學生對事物、現象 的理解。教學( Teaching )的焦點是學生對學習內容的理解 和掌握。教師須瞭解學生想什麼
檢視教科書的 學習材料及活 動,拼音教學 與朗讀訓練同 步施行。. 透過試教及觀 課,觀察學生
價值觀教育須結合學校和家庭教育,學校與家長必須緊密合作,才能
中學中國語文科 小學中國語文科 中學英國語文科 小學英國語文科 中學數學科 小學數學科.
價值觀教育須結合學校和家庭教育,學校與家長必須緊密合作,才能
於 2016 年 12 月發布的《推動 STEM 教育-發揮創意潛能》報告,強調加強學生綜合和應用 不同科學、科技、工程和數學(STEM)