Chapter 2 Literature Review
The research of related work is reviewed in this chapter. Previous studies of using video technology to deliver learning content are discussed in Section 2.1.
Research of using video technology as a learning tool is presented in Section 2.2.
Section 2.3 reviews the related studies of lab-based learning. Research of image processing teaching is reported in Section 2.4. Additionally, related works of learners’
characteristics is detailed in Section 2.5.
2.1 Use of Video Technology to Deliver Learning Content
Video in the twenty-first century is a well-established medium for communication, entertainment and learning. With respect to learning, the advantages of using videos to enhance learning have been documented in prior literature. Park & Hopkins (1993) reported the significance of visual display from two different paradigms: behavioristic and cognitive paradigm. From the view of behavioristic paradigm, visual display has three mainly functional significances. First, it served as a cue for guiding and directing attention. Secondly, an association between the narrated and visual components would draw learners’ attention to instruction, in turn, elicit implicit responses to it. Thirdly, these verbal and perceptual responses would serve as cues in performance on an unprompted or terminal application (May & Lumsdaine, 1958;
Lumsdaine, 1961; Sheffield, 1961). As to the view of cognitive paradigm, dynamic features of visual display bring three attributes, namely visualization, motion, and trajectory of an object, to the instructional setting. By these attributes, complex cognitive tasks could be made more concrete and easy to understand. Furthermore,
audiovisual experiences can heighten students’ awareness and encourage critical thinking skills (Bruning, 1992). On the other hand, the capacity to preserve oral events, allow replay and stop action makes video a good medium to facilitate learning (Duhaney, 2000; Tsutsui, 2004).
Developments in digital technology and Internet, particularly streaming technology, create a new dimension for video-enhanced learning by facilitating learners to use video technology. A learner can easily request a video over the Internet in stead of downloading the whole video file like before. Since the streaming video is sent in a continuous stream, and can be played as soon as it arrives, learners can watch the video before downloading is complete (wikipedia, 2007). Additionally, the function for users to mark a particular position in the streaming video sequence is useful in education application. Advances of technologies have reduced the cost and eliminated many problems to apply video technology in education. Instructors and learners have more opportunities to utilize video technology to facilitate teaching and learning than before. As a consequence, many studies and research on using video technology to deliver learning content have been conducted in past few decades.
The value of video technology to deliver learning content is well recognized.
Video is unique in the use of multiple information streams, such as audio, visual and textual to provide a compelling and immersive educational experience. Instructional video, broadcasted through TV or CD-ROMs were the main medium before the computer network. Integrating video viewing with computer network offers even more practical use of the video resources. The Living Textbook project (Mills, Fox, Shelly, & Bossert, 1995) delivered real-time, multimedia, information on demand for use in classroom instruction. Over 100 hours of on-line searchable video material were put at the teachers fingertips. On the other hand, Interactive Multimedia Distribution System (Jafari, 1996) was used in a university setting in which students
were able to watch archived video materials or television broadcast on campus networked computer.
The practice of taping lecture videos is mostly found in distant education courses.
In which case, the lectures are pre-taped and placed on the course website for registered students such as the research of Haga (2002), Cadiz, Balachandran, Sanocki, Gupta, Grudin, and Jancke (2000). Because taping lecture videos afford students repeated viewing the lecture, and rehearsed material, students can develop deeper levels of understanding, including major topics and minor ones initially ignored (Doran , Benson,
& Longenecker, 1992).
With video streaming technology, many universities began to offer e-Learning courses over the Internet. For example, New Jersey Institute of Technology’s virtual classroom project (Hiltz & Muroff, 2002) offered required courses on-line by putting videotaped lectures on asynchronous learning networks. In this project, it was found that learning online was more effective than learning through in-class lectures. The Carnegie Mellon University’s just-in-time lecture project (Dannenberg & Capell, 1997) also found that video-based instruction had similar learning outcome when compared to in-class instruction. Furthermore, if the lecture videos can be randomly accessed, the learning effectiveness was even better. In another empirical study (Zhang, Zhou, Briggs, & Jr, 2006), learning outcomes of four different learning settings were compared. The compared learning settings were e-learning with interactive videos, e-learning with non-interactive videos, e-learning without video, and the traditional classroom lectures. The results indicated that students in the e-learning environment with interactive videos achieved significantly better learning outcome and a higher level of satisfaction than those in other settings. The above research suggested that the taped lecture videos can be an effective resource for improving learning. At University of Wisconsin – Madison, similar success was reported for using the taped
lecture videos to transform a college level lecture-based course to a lab-based centered course (Foertsch, Moses, Strikwerda, & Litzkow, 2002). Image processing usually consists of many mathematical operation or formula based on signal processing nature (McLean, Graham & Jernigan, 1992; Ageenko & La Russa, 2005). For high school students, understanding these complicated and abstract concepts is difficult.
Visualization of the impact that an operation has on the image is cognitively superior to the plain textual description. For this reason, lecture video is chosen as a suitable media to present learning content in this study.
While much of the discussion about the use of video to deliver learning content focuses on innovative practices in distance education, there is a growing trend towards implementation in traditional learning environment. After-class learning and before-class preparation are two research domains that are worth investigating how to use video technology to enhance their learning outcome.
After-class review is important for successful learning. Prior researches indicated that repeated viewings of explanations on difficult concepts can better understand the contents (Torri, 1994; Ross, Beckman, & Meyer, 1995), better interrelate various scattered topics or lessons (Bransford, Sherwood, Kinzer, & Hasselbring, 1985), and better facilitate reflections on learnt knowledge (Rowley & Hart, 1996), all of which are important to effective learning. As a result, taping in-class lectures and making them available on the Internet affords students with opportunities to review lectures, further comprehend lecture materials, and develop deeper level of understanding, including major and minor concepts that might be initially ignored.
Because of the friendly web interface and developed streaming technology, many web lecture capturing systems were advanced. Lecture Browser system (Mukhopadhyay & Smith, 1999) of Cornell University automatically produces high-quality multimedia documents from live lecture, seminars and other talk. The
system provided user timeline to browse video clips. Forum system (Isaacs, Morris, &
Rodriquez, 1994) was a distributed application. By using Forum instructors can broadcast live audio, video, and slides over a network. At the same time, students can interact with instructor through a number of feedback channels. Flatland (Chesley, Kimberly, White, Gupta, & Drucker, 2001) was a distributed application similar to Forum. Combining Microsoft NetShow streaming audio and video with a collection of feedback mechanisms, Flatland allow the presenter to receive responses from the viewers. Research about Forum (Issacs, Morris, & Rodriquez, 1994) mainly investigated students and instructors’ behaviors during the capture phase of a live lecture. Flatland system (Chesley, Kimberly, White, et al., 2001) was used in distance education. This study examined the reaction of students and changes in operation behavior and perception. Manic system (Padhye & Kurose, 1999) investigated how students accessed the video in an entire semester. Its attention aimed at media usage, such as forward, backward skips times and the workload of media server.
Viewing videos can not only enrich after-class learning, it can also prepare before-class learning, which is also crucial for learning. Before-class preparation provides learner with background knowledge in serves the purpose of reducing the mental loading during in-class lecture. Similar to advance organizers (Ausubel, 1960), in-class preparation is able to activate concepts which are already established in learner’s cognitive structure and thereby facilitate knowledge acquisition. Based on the background knowledge established in before-class preparation, students will be able to effectively structure knowledge when receive in-class lectures or take hands-on activities. By bringing technology to enhance students’ learning before instruction, the in-class time will, in turn, be more efficiently utilized.
Many issues about using video technology to facilitate after-class learning were involved in many research studies as discussed above. However, few studies were
investigated on utilizing video technology to further before-class learning. Reading textbooks is the most taken activity in before-class learning, even no preparation was made before class. Few learning resource and activity were designed for before-class learning. Videotapping lecture video for before-class learning is a good solution. As the result, how lecture videos can be used to facilitate before-class learning, in turn, enhance better utilization of class time is the research purpose in this thesis.
2.2 Use of Video Technology as a Learning Tool
In the topic of using video technology as a learning tool, the extent to which learning activities are used has varied widely, depending on the methodology selected.
According to the role and function that video technology support in learning activities, it can be classified into three categories: as recording tool, as context presentation tool, and as authoring tool.
2.2.1 Recording Tool
The capacity to preserve oral events that allows to replay and stop action makes video as a good media for self-evaluation and giving feedback (Hutchinson, Cissna, Hall, Backlund, & Tolhuizen, 1978; Tsutsui, 2004). Based on the capacity for capturing much of what is happening in the videotape and the availability for repeated viewing, video technology help learners to see what they had not been aware of during the time of the taping. In the traditional in-class learning environment, it is common that students receive feedback from course instructor immediately after their practices.
However, this approach has two limitations. First, students receive limited feedback because of time constraints, with just one instructor to many students and limited class time. The second problem is that students have limited opportunities to reflect on their own practices. Video-support reflection and giving feedback could be a primary solution to overcome the two limitations mentioned above.
The use of video technology has been incorporated into reflection activities widely used in many performance courses, such as teacher preparation, behavior modeling training, and language oral conversation. In teacher education, video technology has been adopted as a means to record teaching modeling to analyze, evaluate, and improve upon individual teaching performance. Rosaen, Lundebery, Cooper, Fritzen, and Marjorie (2008) reported that video-supported reflection enables pre-service teachers to write more specific comments about their teaching compared to reflection drew from their memory. It also helps pre-service teachers shift the focus of the reflections from themselves and classroom management to children and instruction. Wright (1998) reported that video-based self-evaluation provided stimulus for teacher to change their professional knowledge. In the study of Maclean and White (2007), pre-service teachers were required to videotape their own teaching and to discuss with experienced teachers to identify points at which they could have acted differently. The research results suggested that video provides the opportunities for pre-service teachers’
professional learning. Through sharing evaluation of specific actions on the videos, pre-service teachers also shared understandings of what considers as good teacher behaviour. Kpanja (2001) also presented that video-supporting groups showed significant progress in microteaching skills training over the control group who did not use video. The reflective teaching programs conducted in Iowa State University and the University of Alaska used video to facilitate reflection (Kleinfeld & Noordhoff, 1990). Students were urged to assess the context as well as the content of videotaped
sample lessons. They reflected upon the contribution of the situation to the behavior of teachers and pupils. Pailliotet (1995) carried out a deep viewing activity which aimed at discussing teachers’ classroom situation taped on the videos. The results suggested that deep viewing helped teachers to understand the workings of their own classrooms better. .
The advancement of streaming video, incorporation streaming video and communication technology offers reflection and feedback with higher quality. CMC (computer-mediated communication) equipped with discussion channels have been utilized in many research. For example, by viewing video recordings of students’
in-class performances and using CMC to discuss after class, the course instructor can have enough time to give delayed feedback. Meanwhile, students can analyze, evaluate and improve upon individual oral performance after class. It can help students to identify both their strength and weakness in their performance. Wu & Lee (2004) and Lee & Wu (2006) used video-enabled, web based CMC for the provision of feedback to pre-service teachers who were in a Teaching Practicum course. Pre-service teachers’
micro-teaching and field-teaching performances were videotaped and made available for viewing within the CMC system. Experienced high-school teachers were asked to critique the pre-service teachers’ performances and to lead the discussions using the CMC system. The results of the study indicated that the system effectively enhanced pre-service teachers’ teaching experience.
Video-supported reflection activities have also been extensively designed in medical education. Amanda, Michael, & Gregory (2007) assisted medical students to assess their own developing communications skills by viewing videotapes of their interaction with simulated patients. It was found that students tended to achieve tasks and skills relevant to effective communication and relationship building. Cameron and McMillan (2006) encouraged general practitioners to develop communication skills by
peer review of consultation videos. Results of the research confirmed that video is an effective tool in promoting change in consulting behaviour and developing peer review.
Participants welcomed the availability of further technical advices through the practicalities of videotaping. In Kalwitzki’s research (2005), undergraduate dental students were filmed onto video tapes for latter reflection whilst performing paged iatric treatments. Many students indicated that watching the video had made it easier for them to put theoretical knowledge into action. Furthermore, video was useful for improving capacities to deal with patients in fear or pain and for ergonomics. Hansebo and Kihlgren (2001) used video-recording to facilitate carers to take reflection on their interactions with patients suffering from severe dementia. Video-supported reflections enable carers to examine decisions and make them aware of the knowledge that has evolved in the practice. The research findings suggested that the extent of carers’
reflection was improved. More awareness and knowledge of their own qualifications of being health cares were found.
Similar research was also investigated in behavior modeling trainings. In Decker’s study (1983), students were required to reproduce a model performance based on viewing a videotape. It was found that videotaped feedback enhanced scores to teach proper behavior in on-the-job-training of college students. This kind of feedback also has been used in the field of medicine to help doctors self-evaluate their abilities to convey information to cancer patients (Meerwein, Beck, Bernhard, Burgin, Dreifuss, &
Egli et al., 1991), or in the dental education to reinforce skills of presenting information to child patients and their parents (Davis, Tedesco, Nicosia, Brewer, Harnett, & Ferry, 1988; Waggoner & Schneid, 1989). In physical education courses, Mohnsen and Thompson (1997) used video in documenting and modeling performance as well as for self-analysis in the learning process. In Lifesign project funded by Joint Information Systems committee (Green, Voegeli, Harrison, Phillips, Knowles, Weav et al., 2003),
video was used to increase opportunities for independent and self-directed learning in life sciences course for student nurses. It incorporated tasks designed to encourage students with video, such as answering a set of questions, drawing diagrams based on information from the video, producing summary notes, and linking video content with material from recommended textbooks. Another application is on-the-job training.
Decker (1983) found that videotaped feedback enhanced scores in a program to teach proper behavior in on-the-job training to college students. These research results suggested that streaming video can contribute to better useful resources to support learning.
In language performance course such as oral conversation, public speaking and group discussion, giving students opportunities to practice, providing appropriate feedback and taking reflection are very important (Quigley & Nyquist, 1992).
Viewing a video of one’s language performance will stimulate to recall the performance, which in turn produce reflection on his pronunciation, and speaking, which will directly lead to efficient language learning. Providing feedback in language performance course has three purposes: (a) it can inform speakers about the audience’s reaction to the speech; (b) it can make suggestions for improvements on future speeches; and (c) it can motivate speaker to speak again or to enjoy speaking (Book, 1985). It is easy to destroy students’ confidence with too many interruptions (Burt, 1975). Thus, delayed feedbacks, as opposed to instructive feedbacks, meaning to provide comments after the performance could be more suitable to comment students’ in-class oral performance.
Video is suitable as a means to give delayed feedback. Furthermore, reflection enables students to monitor their speech patterns, acknowledge correct utterances, and thus enhancing their professional growth. It is a means to not only enhance classroom practices, but also motivated language learner (Pennington, 1992). Therefore, providing feedback and opportunities to self-reflection is important for students to
practice oral performances.
Viewing recorded in-class performance video on line after class is a good means to provide feedback and take reflection. Hada, Ogata, and Yano (2002) developed a video correction system to record the conversation and edit for later reuse for enhancing explanations and comments about pronunciation and intonation. Chiu, Lee, and Yang (2006) effectively adopted video to facilitate oral conversation drills. Students’
in-class oral conversation drills were videotaped and made available for viewing on a CMC system. After each class, students and course instructor can give both textual and audio feedback to each student’s in-class oral conversation drill on CMC system to foster interactions, which were limited in the classroom due to the constraint timeframe.
As a result, more peer interactions after class become possible.
2.2.2 Context Presentation Tool
Video technology provides instructors with a means of presenting material in a time-efficient and compact manner, and of stimulating students' senses, thereby helping them to process information more readily. Particularly for its authentic forms, video technology which can captures audio, and real-life images are suitable for presenting case stories, or scenarios to provide rich contextual information.
The use of video technology to present case stories or scenarios can be found in situated learning, and case-based instruction which require discussion, problem solving and collaborative learning activities. These approaches engage students in a complex, realistic environment to solve problems and make decisions not easily learned from a textbook or traditional lecture-based instructional environment. Repeated viewings and reflections are crucial for the understanding of a complex contextual environment in
these approaches. Video technology which enables random access, presenting information in a complex way and viewing iterations benefit the implementation of situated learning and case-base instruction. Researchers (Kinzer & Risko, 1998) claimed that random access video is preferable to other delivery system by comparing the differences between print, video, and random access delivery systems for case-based instruction.
Situated learning and case-based approach has taken more attention and becomes increasingly popular over the past several years (Lundeberg, 1999; Jonassen &
Hernandez-Serrano, 2002). One famous example is the Jasper adventure series produced by the Cognition and Technology Group at Vanderbilt (CTGV). Jasper series (eg, CTGV, 1991, 1992, 1993) use video to present authentic contexts and challenges that characters face in case stories. Students similar to the characters in the video scenarios were engaged in the real problems presents in the video. Following the Jasper, many researchers (Shyu, 2000; Hung, Tan, Cheung, & Hu, 2004) applied video-based narrative to support problem solving activities. These research successfully used videos as anchors which function as a macro-context for the learners.
These findings suggest that video-based anchored instruction provide a more motivating environment that enhanced students’ problem-solving skills. Therefore, the development of these video technologies serves as support to such instructional strategies.
Many domains, like medical, ethics, and teacher education have also used video cases for instruction. In the area of medicine, for example, professors may present students with several video medical cases and ask for their diagnoses while watching it (Dequkker & Faspaert, 1998). The advantage of a video case is that the patient is always available. Moreover patient’s story can meet the competence of the staff members present at the presentation and discussion. Video cases are also used for
ethics issues in accounting education. Homer & Steeck (1989) suggested that video cases are very useful for discussing ethics in the classroom. Awasthi and Staehelin (1994) found that the video cases helps students understand how management accountants can play a proactive in promoting the ethical environment in a firm, and appreciate the role of accounting in organizations. Students in these research felt watching the video interesting and showed actively participation in the class discussion.
The use of video-based cases for teacher education has been advocated by many researchers (Merseth & Lacey, 1993; Pape & McIntyre, 1993; Copeland & Decker, 1996). Video cases are used as a vehicle for assessing the novice teachers’ observation skills. Pape and McIntyre (1993) provided video cases for pre-service teachers to observe unique situations that they might encounter in the classroom. Pre-service teachers were required to comment on significant events using the course concepts as a base for knowing what to observe and what to comment on. Additionally, they had to make judgments regarding the teacher’s behavior and interaction with the students presented in the video cases. In this research, pre-service teachers indicated that video case observation provides them more realistic opportunity to implement the experiences, knowledge, and skills of classroom teaching. Schrader, Jr, Kinzer, Ataya, Teale, Labbo, and Cammack (2003) investigated the effects of video cases on pre-service teachers’
learning by comparing three instructional treatments: traditional, traditional plus video cases, and traditional plus online video cases. No significant differences were found for any of the three treatment conditions on the concept mapping task or the confidence measure. However, further qualitative analysis revealed that the use of online video cases takes great challenges and benefits than traditional treatment.
In language learning, video effectively creates a contextualized situation within which language items are presented and practice (Brinton, 2001). As Swaffar and Vlatten (1997) pointed out, video provides both visual and auditory messages for
learners to improve listening comprehension. A parallel view was taken in the evaluation of video teaching by Schrum & Glisan (2000), stating that video provides the context for a wide variety of communicative and interactive activities in the classroom.
Thus video appeals to students' senses and help them process information, thus empowering their understanding of the target culture and increasing their motivation toward language learning, reinforcing the teaching points, and saving the teacher unnecessary explanation. On the basis of the schema theory, Altman (1990) suggested that video serves as a perpetual advance organizer, which offers the constant assistance of images for the process of schematizing and helps students to decode the difficult oral text. Terrell (1993) concluded three benefits of video materials in foreign language learning: to lower the subjects' inhibitions when engaging a native speaker in the conversation, to improve of understanding in real conversations, and to enhance the speaking ability. The research results (Secules, Herron & Tomassello, 1992; Terrell, 1993; Swaffar & Vlatten, 1997) also showed that a video-based curriculum could support the development of listening comprehension skills. Another advantage of video is that the visual support and association of image enable learners to better contextualize and enhance recall. In a survey conducted by White, Easton, and Anderson (2000) regarding students’ perceived value of video in a language course, it was found that video not only could contribute to the acquisition of listening, speaking skills, and pronunciation, but also could help recall by the visual setting and the overall context.
2.2.3 Authoring Tool
Utilizing new advanced digital video technology, such as video authoring, edition
and annotation, broadens the spectrum of the existing video use paradigms. Stanford Center for Innovations in Learning of Stanford University developed a video creation and edition system, namely DIVER (Pea, Mills, Rosen, Dauber, Effelsberg, & Hoffert, 2004). DIVER enables users create new digital video clips from any video record and comment on video by writing short text passages or codes. By using virtual camera, users can zoom and pan through space and time within an overview window of the source video. It helps to develop skills of observing, noticing details and enhancing the collaborative processes. DIVER can be used to promote the development of professional vision in learning within disciplinary domains. Another similar system is HyperVideo system developed by Computer Graphics Center and Knowledge Media Research Center of Muenster University (Chambel, Zahn, & Finke, 2004). Users of the HyperVideo system can annotate within video materials by adding multiple links which include data files uploaded from a local computer and URLs. It enables the linking of video information which helps users to establish non-liner information structure and focus their attention in collaborative learning on associated concepts.
Therefore, users can include their own annotations and knowledge in a video and share them with others. HyperVideo has been used in many courses to support contextualized learning.
2.3 Lab-based Learning
While there are many different approaches to enhance students’ learning, lab-based learning approach has gained popularity in recent years. Labs offer many advantages over traditional in-class lectures. Labs can be used to facilitate exploration and illumination of difficult concepts (Knox, Wolz, Joyce, Koffman, Krone, Laribi et al., 1996). Furthermore, labs can promote students’ cognitive activities in comprehension
and application in terms of Bloom’s taxonomy (Doran, & Langan, 1995). Typically, students are encouraged to discuss or even work together on a problem in lab.
Students often help each other by explaining learned concepts to peers. In so doing, students can become comfortable with collaborations (Prey, 1995). Their observation skill, operation skills, problem solving abilities, and learning attitudes are also improved at the same time (Hofstein & Lunetta, 1982; Okebukola, 1986). Most importantly, lab activities consist with the concept emphasized by constructivism theory - learners construct knowledge actively rather than passively receive knowledge. Labs can enhance students’ cognitive learning, which is often elucidated as the integration of theory with practice (Edward, 2002).
In addition to the advantages and importance of lab-based learning approach mentioned above, using visualization and simulation software in lab activities can help conceptualize abstract content, which in turn improve comprehension. Colaso, Kamal, Saraiya, North, McCrickard, and Shaffer (2002) pointed out that visualization software can stimulate learning and further help to store the knowledge in long term memory.
Positive pedagogical results can also be achieved when utilizing visualization tools to demonstrate the basic concepts and each step of algorithms (Stasko, Kehoe & Taylor, 2001; Rosling & Naps, 2002). More vivid than textbook, visualization and simulation software integrating pictures, slides, and animations would promote students’ learning motivation and interest (Saraiya, 2004). For the merits mentioned above, visualization and simulation software are widely used in lab activities to enhance better learning outcomes.
Lab-based learning approach is largely applied not only in traditional science course learning, such as Physics, Chemistry, and Biology, but also in Computer Science courses. Many design and research of lab classes and lab visualization software in computer science education have been reported. The research (Canas, Bajo, &
Gonzalvo, 1994; Boroni, Eneboe, Goosey, Ross & Ross, 1996; Lee & Wu, 1999) focused on using lab to teach Programming Language. Lin, Wu and Liu (1999) designed lab software for Computer Architecture. Many researchers (Wu, Lin, & Hsu, 1997; Gustafson, & Kjenoli, 1998; Jarc, 1999; Ierardi, & Li, 2001; Gogeshvili, 2002;
Cappos, & Homer, 2002; Dershem, McFall, & Uti, 2002) developed Data Structure software. Furthermore, lab tools for Algorithm learning were implemented in other studies (Duane & Michael, 1998; Barbu, Dromowicz, Gao, Koester & Wolf, 1998; Zeil, 1999; Robling, 2001; Rodger, 2002; Stern, 2002). Positive results in these and many other studies (Parker, Cupper, Kelemen, Molnar & Scragg, 1990; Thweatt, 1994; Oliver
& Dalbey, 1994; Knox, Wolz, Joyce, et al., 1996; Doran & Langan, 1995; Prey, 1995;
Lin, Wu, & Liu, 1999; Lee & Wu, 1999; Lischner, 2001; Edward, 2002) gain labs-based model a crucial place in computer science education.
Ever since the Computing Curricula 1991 (ACM/IEEE Joint Task Force, 1991) and its sequel Computing Curricula 2001 (ACM/IEEE Joint Task Force, 2001), recommended that laboratories be an integral part of undergraduate computing curricula, labs have become a major topic for discussion in the ACM SIGCSE Technical Symposium. In recent years, more textbooks for college computer science courses, especially the introductory courses, are now providing lab manuals and exercises as a necessary supplement. However, this trend has not spiraled downward to high school computer science education. Furthermore, with limited class time, it is a challenge to give the lecture and to conduct lab all in one class period. In this study, the research look to revamp the current practice in Taiwan’s high schools for teaching and learning of advanced applied fields of computer science from that of in-class software-based lectures approach to that of lecture video facilitated lab-based approach.
2.4 Image Processing Teaching
In the literature, two ways of utilizing technology to facilitate image processing teaching are explored: 1) students writing their own programming, and 2) students applying developed visualization software in image processing course. In the first case, students are expected to implement and test image processing algorithms by writing programming codes. As to the latter, students operate and observe the visualization software developed by many researchers to enhance image processing concepts.
MATLAB and Khoros are two popular programming environment for coding image processing programs. Because of the powerful graphic and simple functionality, MATLAB (MathWorks, Inc., 2007) has been widely utilized as education tool for image processing teaching in recent years (e.g., Eddins & Orchard, 1994). MATLAB is an integrated computing environment which applies a combination of graphics, visualization, and a high level programming language. The distinguishing feature of MATLAB is matrix data structure, which makes it perfect for image processing.
Image processing operations that might require many lines of code in other languages, such as C or Fortran, can be expressed in a single line of MATLAB code. Because of the widespread popularity of MATLAB, MATLAB-specific computer exercises have been included in textbook of Image Processing (e.g., Burrus, McClellan, Oppenheim Parks, Schafer & Schuessler, 1994). In addition to general image processing teaching, researchers (Uppuluri & Jost, 2004; Jost & Uppuluri, 2005) also implemented toolkits by MATLAB suitable for classroom use to illustrate the principles of image processing in specific domain.
As for Khoros, it distributed through the Internet as free access software is a software integration and development environment that emphasizes information processing and data exploration. “Cantata” is a visual programming environment in
Khoros which is suitable for image processing learning. The cantata data flow visual language, combined with the 200 image processing programs, allows the users to master abstract image processing programs. Moreover, in Khoros, image processing tasks are composed of a variety of primitive data operators. Users can connect existing operators and create more complex operator to develop image processing algorithms.
Thus Khoros enables users to design, simulate and quickly test hypothesis in image processing learning. Many research (Rasure, Jord’an & Lotufo, 1994; Konstatinides &
Rasure, 1994; Jord’an & Lotufo, 1996; Donohoe & Valdez, 1996) have done to use Khoros as a facilitator for image processing teaching.
Although MALTAB and Khoros provide many pre-assembled functions and image processing toolbox, users are still required programming skills and knowledge of the techniques to implement. It is overloading and time-consuming for students, especially the non CS-major ones. They may spend much more time on coding and debugging instead of thinking about the important concepts and theories involved in image processing procedures. For reducing these requirements, many packages and software for image processing learning were developed so that students can conduct in-depth exploration and experimentation without programming. The followings are introduction of packages for image processing learning developed in recent years.
Package 1: AVS Express (Sohi & Devgan, 2000)
AVS Express (Advanced Visual Systems Express) (Sohi & Devgan, 2000) provides many modules corresponding to image processing operations in a visual programming environment. Users are allowed to drop the modules into a workspace and assemble these modules into a network to perform the required operation of image processing.
Users can not only see the flow of information of the different algorithms as they are being implemented, but also easily detect the errors indicated by lighting up the
connection between two modules. Thus no time is spent in writing programming and debugging. Due to AVS Express’s drag and drop interface, it saves much time to implement image processing techniques in AVS Express than in MATLAB. AVS Express has been integrated in Digital Image Processing course as a teaching aid at Tennessee State University.
Package 2: RLE, Quadtree, and JPEG (Khuri & Hsu, 2000)
Khuri and Hsu (2000) developed three interactive packages for learning image compression algorithms: RLE, Quadtree and JPEG. RLE and Quadtree demonstrate bitmap image compression algorithms, whereas the third package, JPEG, visualizes the Joint Photographic Expert Group (JPEG) standard. These packages animate image compression algorithms by displaying different states of execution, and providing textual explanations to help users understand the visualization.
RLE is a package for run length encoding algorithm. It provides five compression algorithms: column by column, row by row, zig-zag, Hilbert Space Filling Curves, and Sierpinski Space Filling Curves. Students can manipulate the image files by employing different compression algorithms and compare which files or which algorithm compress better. Quadtree aims to demonstrate the quadtree compression algorithm for bitmap images. It takes a bitmap as input, and shows how the quadtree algorithm partitions the image. Once the algorithm has reached the stopping criterion, this package will display the number of leaves and interior nodes of the quadtree, as well as the compression ration. The third package, JPEG, uses text, graphs, and interactive examples to tutor how JPEG compression algorithm works. Each procedure and step of JPEG algorithm including color space transformation, discrete cosine transformation, quantization, and entropy encoding are explained. Because of the variety of algorithms, from simple to complicated ones, these three packages were also used in Data Structures, Algorithms and Data Compression course as well as Image
Processing course.
Package 3: Toolkits for image enhancement and face recognition (Marks, Freeman,
& Leitner, 2001)
Marks, Freeman, and Leitner (2001) employed case studies to teach two topics of image processing concepts: image enhancement and face recognition, to non CS-majors in college. Two lectures involved in the teaching of each case study: firstly presented an intuitive overview of the basic concept of image processing and the second concentrated on hands-on application operation. In the case study of image enhancement, instructor firstly introduced simple methods to modify the tonescale, sharpen and de-noise images. Students then enhanced several supplied images and simulated the image-processing steps by Adobe Photoshop to study these image-enhancement operations.
As in the case study of face recognition, many fundamental visual measurements including tracking, shape and object recognition, and motion analysis were firstly reviewed. Additionally, students also learned how to measure performance for recognition task. One face recognition software and a small database of 40 images of faces of volunteers from the class were provided in second lecture to study the effect of different image-similarity metrics on face-recognition performance. After the hands-on practices, students were demonstrated that the recognition performance mainly depends on lighting, facial expression, and head pose. This research has two purposes:
1) Students perform design and problem-solving tasks by hands-on software, therefore reinforcing the abstract concepts presented in first lecture. 2) Students conduct in-depth exploration and experimentation without writing any programs which is a difficult job for non-major students. The course involved these case studies has been offered for two years at the Harvard University Extension School. At the end of the project,
students showed their favor and gratitude on the learning experience.
Package 4: SIVA (Rajashekar, Panayi, Baumgartner, & Bovik, 2002)
Rajashekar, Panayi, Baumgartner and Bovik (2002) together developed SIVA (Signal, Image and Video Audiovisualization Demonstration Gallery) for signal- and image-processing courses in the University of Texas at Austin. SIVA comprised of two visualization modules: LabVIEW-based demonstration suite for an undergraduate course titled “Digital Image Processing and Video Processing” and a MATLAB demonstration package for a graduate course named “Digital Signal Processing”.
LabVIEW is a graphical programming language used as a powerful and flexible instrumentation and analysis software in industry and academic. Through the support of LabVIEW, SIVA developed many VIs (virtual instruments) for illustrating fundamental operations in image and signal processing procedure. The learning topics of VIs include analogy – digital conversion, binary image processing, histogram and point operations, Image Analysis (Frequency Interpretations), directional DFTs, image filtering, image compression, other advanced topics, such as linear and nonlinear filtering, lossy and lossless image compression schemes.
Putting on the Web learning management system, the demonstrations of SIVA are available over Internet. The image/video processing learning courses using SIVA as supplement attracted students from a variety of backgrounds at the University of Texas at Austin. Many other users from various countries also used SIVA for their projects and as a teaching tool for image/signal processing courses.
Package 5: IPT (Ageenko & La Russa, 2005)
IPT (Image Processing Toolkit) (Ageenko & La Russa, 2005) is a visualization tool to demonstrate various abstract concepts of image processing. Its point-and-click
interface is user-friendly. Users are not only provided many image processing algorithms to interactively apply to image, but also allowed to change the algorithm parameters. The produced effects of the algorithm on the image can be immediately observed and compared with the original one. By synchronous panning and zooming, IPT helps to demonstrate how algorithms and their properties differentiate on the image by giving an immediate comparison of the images. Different image types, binary, grayscale and color image, are supported in IPT. Importantly, IPT is a standalone tool and has open application interface based on Java platform. Therefore, new image processing algorithms implemented by any researchers can be added as plug-ins to the toolkit to enrich its features and functionalities.
As mentioned above, many common features are shared in these packages. First of all, many algorithms were provided in the packages or can be added into the system, to assist users to explore the image processing theory without programming. Secondly, user-friendly interface is necessary in the package environment. Last but not least, being able to execute in different platforms is inevitable. These features are worth to be considered in future studies. It is also worthy noticing that these packages were designed to facilitate image processing learning in undergraduate or graduate level.
The topics covered in the packages might be too advanced and less suitable used in high school level. More attention of image processing learning is needed to take for high school. In this thesis, development of image processing packages integrated in lab activities for high schools’ image processing teaching is one of our purposes.
2.5 Learners’ Characteristics
Learners’ characteristics usually influence their learning behavior. This section reviews related research on two types of characteristics: computer self-efficacy and
learning motivation.
Self-efficacy is defined as an individual’s judgment of his or her own capability to perform a particular task (Bandura, 1977). It might have an impact on how much effort an individual is willing to invest in and what strategies to take when encountering challenges or difficult problems that may affect students’ academic achievement (Bandura, 1996). Computer self-efficacy includes general computing knowledge and some specific application skills. It has been found to be positively related to performance in software training (Martocchio, 1992, 1994; Rozell & Gardner, 1999;
Webster & Martocchio, 1992, 1993, 1995), academic performance in introductory MIS classes (Karsten & Roth, 1998; Rozell & Gardner, 1993), and adaptability to new computing technology (Burkhart & Brass, 1990). Application-specific skill is one’s perception of efficacy in using a specific computer application or system (Marakas, &
Johnson, 1998). Previous research (Ames, 1992; Brown, 2002; Tsai, & Tsai, 2003; Yi,
& Hwang, 2003) revealed that application-specific self-efficacy has a positive effect on using information technology for learning.
Application-specific self-efficacy is particularly important in the online distance courses. Because students are physically separated from the instructor and peers in this learning environment, they take more responsibility for their learning, including handling of any technical difficulties. Students with greater application-specific self-efficacy are more likely to have more confidence in handling these difficulties on their own. Consequently, students with higher computer self-efficacy might have positive attitudes toward online distance courses. For such reason, in this study, application-specific self-efficacy is used as a scale to measure a student’s individual characteristics when using an online lecture video browsing system. The relationship between application-specific self-efficacy and lecture video viewing behaviour is a focus of this study.
Learners’ motivation to learning is another learner characteristic that can have much weight on learner’s learning. Many studies have reported a positive correlation between learning motivation and achievement in traditional learning environment (Lukmani, 1972; Noels, Clement, & Pelletier, 2001; Peng, 2002). Researchers (MacIntyre & Noels, 1996; Peng, 2002) further found that motivated learners made better use of learning strategies and achieved higher proficiency.
In the research domain of web-based learning system, students’ use of such systems for learning are usually voluntary or not required, so that students’ learning motivation might be related to their system usage and achievement. In the research of Oxford, Park-Oh, Ito, and Sumrall (1993) indicated that motivation affected performance in a foreign language course delivered by distance education. Shih and Gamon (2001) analyzed the relationships among students’ motivation, attitude, learning styles and achievement in two web-based courses. They found that motivation was the only significant factor that determined student achievement. The research in Grabe (2005) examined the differences in students’ learning motivation in the context of voluntary use of online notes. The results showed that frequency users of voluntary use of online lecture notes in an Introductory Psychology course in the college had significantly higher extrinsic learning motivations toward the course than those who frequently used notes as a replacement for class attendance. Roberts and Dyer (2005) explored the relationship between self-efficacy, motivation, and critical thinking disposition to achievement and attitudes when a web lecture is used in an online learning environment. The results indicated that motivation and computer proficiency tend to influence attitudes and that motivation and prior knowledge influence achievement. It was concluded that when a web lecture is used to deliver content, students with higher levels of motivation tend to exhibit higher achievement and more favorable attitudes. Although the previous studies have analyzed the relationship
between learning motivation and web use or achievement in web-based learning environment, whether students’ learning motivation affected their online lecture video viewing behaviour was not examined. More research is needed to investigate how learning motivation influence students’ intention to view lecture videos before class.
Thus, in addition to application-specific self-efficacy, students’ achievement goals are also to be identified in this study.
In the present study, achievement goals were used to measure students’ learning motivation. . Achievement goals include mastery goals and performance goals. The former is an individual’s desire to master the domain knowledge whereas the latter emphasizes the degree to which someone focuses on his or her performance capabilities relative to others (Brown, 2002). These two goals may influence students’ motivation to learn. Students with high mastery goals would like to develop new skills, try to understand their work, or achieve a sense of mastery based on self-referenced standards (Brophy, 1983; Harackiewicz, Barron, Tauer, Carter, & Ellio, 2000). In contrast, students with high performance goals focus on doing better than others who may apply short-term learning strategies and avoid challenging tasks (Brophy, 1983; Harackiewicz, Barron, Tauer, et al., 2000). It has been shown that mastery goals can positively predict subsequent interests in a course and the performance goals can positively predict grades, but not interests (Harackiewicz, Barron, Tauer, et al., 2000).
