Effect of metacognitive strategies and verbal-imagery cognitive style on biology-based video search and learning performance

Highlights

• Metacognitive strategy is the primary influencer of video search.

• Keyword usage had a significant influence on the students' search and learning performance.

• Students who tend to imagery style preferred watching videos regardless of whether the video content was related to the task.

• Our results are different from previous studies on text, image, and map searches.

• Users must adopt different search strategies when using various types of search engines.

Abstract

Videos have diverse content that can assist students in learning. However, because videos are linear media, video users may take a longer time than readers of text to evaluate the context. Therefore, the process of video search may vary from one user to another depending on the users' individual characteristics, and the effectiveness of video learning may also vary across individuals. This study evaluated 100 Taiwanese fifth graders searching for videos related to “understanding animals” on YouTube and examined the effects of the students' metacognitive strategies (planning, monitoring, and evaluating) and verbal-imagery cognitive style on their video searches. The observable indicators were quantitative (search behaviors, search performance, and learning performance) and qualitative (search process observations and interviews). The study concludes that metacognitive strategy is the primary influencer of video search. Students with better metacognitive skills used fewer keywords, browsed fewer videos, and spent less time evaluating videos, but they achieved higher learning performance. They reviewed the video metadata information on the user interface and did not attempt to watch videos on the video recommendation lists, particularly videos that were irrelevant to the task requirements. During the course of the searches, keyword usage had a significant influence on the students' search performance and learning performance. The fewer keywords the students used, the better search and learning performance they were able to achieve. Our results are different from those of previous studies on text, image, and map searches. Accordingly, users must adopt different search strategies when using various types of search engines.

Introduction

Web information retrieval has become one of the main sources for computer-assisted learning and digital materials. There are an increasing number of different formats for web information, including text, images, music and video (Tjondronegoro, Spink, & Jansen, 2009). In earlier years, students could only access texts due to constraints of network bandwidth and technology. Recently, the number of different multimedia formats has greatly increased. With the proliferation of video/music sharing websites (such as YouTube) and the spirit of sharing and reproducing of Web 2.0, the number of short films shared on these databases has shot up to the millions. These websites provide easily accessible channels with user-friendly platforms to inundate students with video information. In addition to providing entertaining content, these videos serve as educational materials and teaching tools (Nikopoulou-Smyrni and Nikopoulos, 2010, Zhang et al., 2006). Asensio and Young, 2002, Champoux, 1999, Clark and Paivio, 1991, Karppinen, 2005, Mayer et al., 1995, Smeaton and Browne, 2006, and Torres-Ramírez, García-Domingo, Aguilera, and de la Casa (2014) noted that scientific concepts are sometimes too abstract or complicated to be comprehensible. However, the right visual videos (e.g., that show a real animal or a live chemistry process) can help students grasp a concept completely and accurately. Videos can serve as tools that provide multiple presentation and browsing methods (e.g., consecutive scenes, voice for explanations and subtitles for text descriptions). Videos stimulate multiple senses and effectively crystalize abstract concepts using a combination of visuals, text, voice and music. An effective knowledge constructor can actively select and connect pieces of visual and verbal knowledge (Mayer, 1997). Comprehension depends on the successful storage of these connections along the two forms of mental representation (verbal and visual) of these propositions or ideas in long-term memory (Plass, Chun, Mayer, & Leutner, 2003). Therefore, videos can help students comprehend and memorize information, improve their cognitive processes and enhance their learning performance.

Training students how to retrieve information from the Internet for learning is important to teaching them how to utilize Internet technology and information (Clifton and Mann, 2011, Kuo et al., 2012, Laxman, 2010, Sun et al., 2014). Because different types of search engines require different search and cognitive processes, it seems reasonable to consider search engines within three types of formats: text, image, and video searches. Text searches require the comprehension of connotations of a given topic and the use of related ideas to formulate keywords. Because it is easy for students to focus on and search for information via definitive keywords, it only takes them a few searches to retrieve the correct documents or answers. In contrast, picture or image searches require theme formulation and the ability to envision the potential results. Given that many current image retrieval systems are keyword-based, users must translate their visions into literal descriptions, and the pictures stored in databases must have descriptive words or metadata that match the selected keywords (Fukumoto, 2006, Hou and Ramani, 2004). Search systems transmit some pictures for users to compare, assess, and decide whether they need to continue a search. Accordingly, image searches can be analyzed as mixed acts of image-text cross-referencing, observation, judgment, decision-making, and correction. Note that the existence of semantic gaps and the lack of precise characteristics make image searches more abstract and complex than text searches (Choi, 2010, Cunningham and Masoodian, 2006).

In terms of video searches, because videos encompass various formats, evaluating whether video content fulfills users' expectations takes longer than searching for texts and images. Furthermore, in digital environments, the supplementary tools provided by search engines may also influence search behaviors, strategies and performance. Video search engines provide a less frequently observed tool than other types of search engines: the video recommendation system (see Fig. 1). This tool “recommends” other videos that are considered pertinent to the watched video (irrelevant to keywords) for the users' reference by analyzing the search process of individual users and the knowledge structure within the system (Davidson et al., 2010, Zhou et al., 2010). This function is common on video and music sharing websites. The design aims to provide convenience for users rather than helping them learn better. Thus, it may be an additional significant factor in the video search process. Retrieved videos may come from the suggestion of users based on the relevance of the pictures and the texts, and they may also be contributed from recommendations made by the system. In terms of learning, we must be careful to distinguish whether search results are selected by the students or suggested by the system. Will the recommendations of the system be a distraction if the students use improper keywords or view irrelevant videos? A “video recommendation system” can provide both benefits and risks to users. It allows users to quickly browse videos related to the topics that they care about, but it can also lead users to watch a series of videos that are irrelevant to their original search target, which may cause the users to believe that such search results are useful. Thus, when evaluating learning effectiveness in the course of video search, we must take this function into consideration. In sum, the similarities and differences between the three types of search engines are presented in Table 1. Different types of search engines may lead diverse factors to influence search behaviors, strategies and performance due to different search and cognitive processes. Video search is no exception. However, to date, few researchers have made the effort to explore the video search process (Albertson, 2010a, Burke et al., 2009, Clifton and Mann, 2011, Lee and Lehto, 2013, Snelson and Elison-Bowers, 2009, Torres-Ramírez et al., 2014, Uzunboylu et al., 2011). This study aims to analyze and define the individual characteristics that affect students' abilities to effectively use video search engines.

Previous studies have proposed that information-seeking behaviors are complex cognitive processes (Laxman, 2010, Lin and Tsai, 2007, Walraven et al., 2008). Before embarking upon any meaningful search activities, a searcher must understand the questions that they have or the nature of the search tasks by means of the searcher's existing knowledge. The searcher must decide the approximate location of the target in the cyber world (for example, the user must decide between searching general webpages, news articles, blogs, videos, pictures, or maps) and choose a search engine. Then, the searcher can formulate keywords for the search. In the course of the search, the searcher must input a keyword and then review each video from search result lists or video recommendation lists. If necessary, the searcher must move on to subsequent searches after an assessment, during which the searcher may be required to modify techniques, adjust keywords or rephrase questions to better achieve the desired purpose. The entire search process comprises planning, monitoring, evaluating, and revising activities. These are metacognitive learning strategies (planning, monitoring, and evaluating strategies; Brown, 1987) and also a self-regulated learning process (planning, practice, and evaluation; Zimmerman, 1995). Planning a search and understanding the search tasks are highly related to “planning”. Entering keywords and watching videos are part of “monitoring/practice”. Comparing and selecting relevant videos refer to “evaluation”. Therefore, we believe that metacognitive strategies are the critical roles for video search. How users' metacognition influences their search behaviors and performance, however, is not well understood. Therefore, investigating whether metacognitive skills are key influencers in the course of video search and how they influence one's search and learning processes are the main goals of this study.

In terms of media features, videos include symbolic (such as visual text or auditory text), imagery (such as pictures and animations), and vocal (such as music and sound) messages. How each of these messages integrates with the others and is used by individuals is also important for us to understand students' cognitive and search processes. Some people are more advanced in handling words, whereas others show better performance in handling images (Mayer & Massa, 2003). Each individual has a preference for words or imagery that results from the varying amount of time required for them to process nonverbal and verbal symbols. Videos include both of these types of knowledge representation. Subject lines, summaries, thumbnails, and the type of information provided by search engines as well as the narration, animations, and subtitles in videos are all very important information for users (including viewers and those searching for information). When different users are exposed to video, do they prefer verbal or visual representations? Which representation can users process more efficiently? This study adopts Riding and Cheema (1991)'s verbal-imagery cognitive style (VICS) to investigate this issue because VICS may be related to the speed of the encoding process referred to by Paivio, 1971, Paivio, 1986 dual-coding theory (DCT). Does students' cognitive style make a difference in their search behaviors and performance? This study also addresses this question.