ORIGINAL RESEARCH ARTICLE

Animating student engagement: The impacts of cartoon instructional videos on learning experience

Chelsea Liua* and Philip Elmsb

aAdelaide Business School, The University of Adelaide, Adelaide, Australia; bFaculty of The Professions, The University of Adelaide, Adelaide, Australia

(Received: 30 July 2018; revised: 13 February 2019; accepted: 14 February 2019; Published: 1 April 2019)

Abstract

In the modern age of education, students increasingly demand engaging, customized multimedia content. Animation constitutes a powerful pedagogical tool by combining audio messages with tailored visual cues and graphics, to serve the dual functions of explaining complex concepts and engaging student interest in the learning process. This study explores the use of a series of animated videos to teach advanced accounting at an Australian university. Based on survey responses from 254 undergraduate students over two semesters, we provide evidence of the specific avenues through which animated instructional videos enhance students’ learning experience, including increased engagement and interest, improved understanding and greater flexibility in self-directed learning. Additionally, character design, voice acting and dialogues in animated videos are found vital to improving student engagement. Further, this study offers novel insights into how students from various demographic groups can derive different benefits from the animations. These findings deepen our existing understanding of the pedagogical advantages of animated instructional videos and offer valuable guidance to enable future educators to harness the power of animation technologies to produce effective teaching resources.

Keywords: animations; animated teaching videos; multimedia resources; student engagement

*Corresponding author. Email: chelsea.liu@adelaide.edu.au

Research in Learning Technology 2019. © 2019 C. Liu and P. Elms. Research in Learning Technology is the journal of the Association for Learning Technology (ALT), a UK-based professional and scholarly society and membership organisation. ALT is registered charity number 1063519. http://www.alt.ac.uk/. This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), allowing third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for any purpose, even commercially, provided the original work is properly cited and states its license.

Citation: Research in Learning Technology 2019, 27: 2124 - http://dx.doi.org/10.25304/rlt.v27.2124

Introduction

A key challenge shared by educators is how to engage students while delivering content of a technical, complex, difficult and sometimes tedious nature. Students in advanced-level accounting courses often struggle to maintain their interest in the course materials, which involve abstract concepts and convoluted calculations. Technological advancements offer exciting new opportunities to educators to provide more engaging and effective teaching resources (Gerjets and Hesse 2004; Voithofer 2005). They also bring an increasing demand amongst modern students for engaging, customized multimedia resources to assist their learning (Gorissen, Van Bruggen, and Jochems 2012; Kaufmann and Mohan 2009). The availability of Web 2.0 applications has fundamentally changed the way in which information is disseminated in education (Crook 2012; Greenhow, Robelia, and Hughes 2009; Roschelle and Pea 1999). Specifically, there is an increasing trend amongst universities to provide lecture recordings online (Gorissen, Van Bruggen, and Jochems 2012) and incorporate video resources into their curricula (Kim et al. 2014; Tan and Pearce 2011). Further, as a result of the development of animation technologies over the last decade, the creation of animated videos is no longer a complex feat reserved for the likes of Disney studio artists but is widely accessible to educators and students (Furlong and Davies 2012).

In response to these challenges and opportunities, educators at an Australian university developed a series of animated instructional videos designed to explain complex, technical accounting and business principles in a final-year undergraduate course. As a part of this project, implemented over two semesters, a series of nine animated videos were produced to cover all major topics in the syllabus. The videos, ranging from 3 to 5 minutes in length, provide an overview of the fundamental principles in each topic and explain and illustrate the technical concepts with the aid of graphics and/or real-world examples. This study investigates the impacts of these animated teaching videos on students’ learning process.

Using survey responses from 254 students from two cohorts over different semesters, this study investigates the specific avenues through which animated videos affect student learning, as measured by the level of interest, engagement, enjoyment and ease of access experienced by the students. In addition, we examine the roles of student demographic characteristics, including age and gender, in determining how students utilize the animated instructional videos.

The findings of this study seek to contribute to the existing literature in three important ways. This study is the first to utilize a series of animations as instructional videos in higher education, by combining the dual functions of (1) explaining complex technical concepts (e.g. Kelly and Jones 2007; Lowe 2003; Nelson et al. 2017) and (2) providing engaging context and real-world applications of the principles taught (e.g. Adam et al. 2017; Bassford et al. 2016; Mather 2015). This study adds to the rapidly growing literature on the use of multimedia resources in education (Anderson et al. 2018; Clark, Tanner-Smith, and Killingsworth 2016; Mayer and Anderson 1992; Takacs, Swart, and Bus 2015; Theobald 2017). Secondly, drawing on cognitive theory (Mayer 1999) and John Dewey’s pragmatist conception of learning as a social activity (Dewey 1916; Kivinen, Piiroinen, and Saikkonen 2016), this study provides novel evidence of the multifaceted pedagogical benefits of animated instructional videos and their impacts on student learning. Thirdly, we contribute to the literature that examines students’ individual idiosyncrasies in influencing their learning experience (Johnson et al. 2013; Roschelle et al. 2010; Rosenberg-Kima et al. 2010). We explore the impacts of student demographic characteristics (including age and gender) on the relationship between the use of animations and learning outcomes. The findings from this study also have significant practical implications, enabling other educators to better utilize animation-production technology as a powerful learning and teaching tool.

Literature review and contribution

Teaching videos

‘An age of pictures dictates the use of pictures in class’ wrote Richard Spencer nearly a century ago (Spencer 1938). Since then, the rise of the digital new media has overtaken the print media (Voithofer 2005). The rapid development of Web 2.0 applications has revolutionized the world of learning and teaching (Crook 2012; Greenhow, Robelia, and Hughes 2009; Roschelle and Pea 1999). Visual, audio and video aids constitute an increasingly indispensable component of modern education (Friesen 2011).

Prior researchers have examined the pedagogical benefits of a variety of multimedia teaching resources, including contextual imagery (Baron 2016), audio–visual materials (Kinder 1942; Svenson and Sheats 1950; Wendt and Butts 1962), instructional videos (Clark, Tanner-Smith, and Killingsworth 2016; Homer, Plass, and Blake 2008; Sun and Cheng 2007) and games (e.g. Abdul Jabbar and Felicia 2015; Clark, Tanner-Smith, and Killingsworth 2016; Squire 2006). In particular, multimedia videos have been used for a variety of purposes in higher education, including delivering instructions (Chen et al. 2014; McLaughlin et al. 2014; Tan and Pearce 2011), sharing viewpoints and discussions (Goldman 2004; Kim et al. 2014; Tan and Pearce 2011), providing peer feedback and self-reflection (Jordan 2012) and facilitating industry placements (Taylor 2012).

An increasing number of universities provide lecture recordings or online videos to accompany face-to-face teaching (Gorissen, Van Bruggen, and Jochems 2012; Tan and Pearce 2011). Videos with on-screen instructors are generally considered superior to voice-over–type recordings (Chen and Wu 2015; Lee, Hsiao, and Ho 2014; Lyons, Reysen, and Pierce 2012), as visual cues and social presence are important components of teaching videos (Adams et al. 2014; Lee, Hsiao, and Ho 2014; Lyons, Reysen, and Pierce 2012). In the specific context of accounting education, prior researchers have examined the use of multimedia resources (Chan et al. 2016; Johnson, Phillips, and Chase 2009; Richardson and Louwers 2010), including instructional videos (Daigle, Hayes, and Morris 2014; Holtzblatt and Tschakert 2011; Lento 2017). Lento (2017) finds that voice-over videos facilitate the flipped classroom and help accounting students engage in active learning. Daigle, Hayes, and Morris (2014) use video clips of interviews from daytime television shows to teach accounting students about occupational fraud, documenting improved understanding and knowledge. Even though digital video technologies offer significant new potential to enhance accounting education (Holtzblatt and Tschakert 2011), some researchers observe that accounting academics have not fully embraced the opportunities offered by new technologies (Pincus et al. 2017; Rebele and St. Pierre 2015; Watty, McKay, and Ngo 2016).

The existing literature documents several advantages associated with multimedia teaching videos, including increased student engagement (Loong and Herbert 2012; Roschelle et al. 2010; Tan and Pearce 2011), improved ability to apply the knowledge in problem-solving (Ellis 2004; Mayer 1999) and flexibility to learn at any time and location (Gorissen, Van Bruggen, and Jochems 2012) and at each student’s own pace (Chen et al. 2014; Eysink et al. 2009). Nonetheless, the literature also reveals potential downsides of multimedia teaching resources. Firstly, the high costs of production and development limit their accessibility to educators (Sun and Cheng 2007). Secondly, extraneous details in the animations can distract students from the relevant messages (Homer, Plass, and Blake 2008; Lowe 1999). Thirdly, video viewing is found to be an inadequate substitute for class participation and discussions (Ronchetti 2010).

Animations in higher education

Animated videos constitute a subset of multimedia resources. Animations are an important component of entertainment consumed by children and young adults, which serve educational functions (Anderson et al. 2018; Sproull 1973; Theobald 2017) and influence popular culture (Trifonas 2001). Animated graphics are found to improve learning in various age groups, ranging from young children (Takacs, Swart, and Bus 2015) to high-school students (Loong and Herbert 2012; Roschelle et al. 2010).

Despite the prevalence of cartoon programs, there remains limited research on the use of animations as instructional media in higher education (e.g. Adam et al. 2017; Kelly and Jones 2007; Mather 2015; Tasker and Dalton 2008). In the small but growing body of extant literature, animations have been used for two main purposes: (1) explaining basic concepts or (2) providing real-world context and application of existing knowledge. Firstly, science educators have used black and white animated graphics to illustrate molecular-level movements (Kelly and Jones 2007; Sanger, Brecheisen, and Hynek 2001; Tasker and Dalton 2008; Nelson et al. 2017). For example, Nelson et al. (2017) use animated simulations to explain movements of electrons during the process of diffusion. Similarly, Kelly and Jones (2007) use animated illustrations of molecular structure and dynamics in chemistry teaching, which students report to be useful.

In contrast, the second use of animations is to provide real-world (or simulated) context and examples of technical concepts and principles to enrich the learning process. For example, Adam et al. (2017) develop a series of 36 animated videos at the Stanford School of Medicine in collaboration with four other US medical schools. The videos present stories from fictitious patients to provide real-world application of the technical content taught in medical courses. Additionally, animations can be used to enrich students’ learning tasks and assessments. For example, Bassford et al. (2016) incorporate a realistic, interactive crime scene into science, technology, engineering and mathematics (STEM) courses to engage students in interactive learning. Similarly, in teaching computer programming, Mather (2015) uses an animated virtual landscape in which students interact with robot subjects to complete programming tasks.

However, this body of research has produced inconclusive and contradictory evidence on how animations affect students’ learning outcomes. For example, while some researchers find that animated illustrations or assessments improve student understanding in experimental settings (Lowe 2003; Mather 2015; Sanger, Brecheisen, and Hynek 2001), others show that animated simulations can indeed generate or reinforce misconceptions in science learning (Kelly and Jones 2007; Nelson et al. 2017; Lowe 2003). Lowe (2003) concludes that the effectiveness of animations depends largely on their design.

Importantly, prior studies have largely focused on student learning outcomes, measured by their level of understanding, as a criterion for the success of the animated resources (e.g. Kelly and Jones 2007; Nelson et al. 2017; Sanger, Brecheisen, and Hynek 2001). However, student understanding only captures one aspect of their overall learning experience, namely the outcome. We posit that for students to have a positive learning experience, it matters not only how much they learn, but also how interesting, enjoyable and easy they find the process of learning. Limited prior research has been conducted into these measures of the student learning experience associated with animated resources. We fill this gap in the literature by incorporating these aspects into our investigation.

Distinction between comics, moving graphics and cartoon animations

The definition of ‘animations’ or ‘cartoons’ remains ambiguous in the literature. An important distinction must be drawn between cartoon animations versus moving graphics, which are colloquially referred to as ‘animations’ (following the use of the term by Microsoft’s PowerPoint software). For example, Chiou, Tien, and Lee (2015) examine PowerPoint presentation–style animations that consist of still graphics appearing and moving across the screen. Indeed, prior researchers use the term ‘animation’ or ‘cartoon’ to describe a variety of different multimedia resources, including the following:

In this study, we refer to animations to mean cartoon-style videos with a basic storyline, characters, and dialogues or voiceovers, in which the graphics move in synchrony with the accompanying voice acting and sound effects (e.g. a character’s mouth opens when speaking). This distinction is important, because our cartoon animations can deliver a number of benefits beyond those of simple moving graphics, 3D still images or avatars. Firstly, compared with static images with added movements, cartoon animations enable educators to incorporate more sophisticated visual effects to demonstrate and explain technical, abstract concepts. Secondly, in contrast to 3D still images or black and white illustrations, scripting and voice acting can play an important role in cartoon animations, by introducing storyline and banter into the videos to engage students’ attention and interest. Finally, by presenting recurring characters, animated dialogues and simulated real-world sets and backgrounds, our animation series allows students to immerse themselves into the world created by their educators, which further enhances student interest in the course materials.

Gap in existing literature and contribution

This paper is the first to empirically examine the use of cartoon animations to serve the dual pedagogical purposes of (1) explaining new complex technical concepts and (2) engaging student interest in the learning process. We document novel evidence of the impacts of cartoon animations on university students’ learning experience. Our findings provide significant contributions to the existing literature in a number of ways.

Firstly, we combine two major functions of animations: explaining new complex concepts to students (Kelly and Jones 2007; Lowe 2003; Nelson et al. 2017) and engaging students’ interest with multimedia examples, anecdotes and real-world context (Adam et al. 2017; Bassford et al. 2016; Mather 2015). Unlike the animations developed by Adam et al. (2017), our animations are designed to convey new knowledge to students, who are exposed to these concepts for the first time, rather than to reinforce or apply existing knowledge with (simulated) real-world anecdotes or interactive tasks (Bassford et al. 2016; Mather 2015). Further, unlike the black and white animations for science teaching that illustrate molecular movements (e.g. Kelly and Jones 2007; Mayer 1999; Nelson et al. 2017), our animations serve the additional function of providing real-world examples and context while engaging students with storylines and dialogues. Our evidence demonstrates that both engaging student interest and enhancing their understanding of the subject matter constitute important avenues for animated videos to improve students’ overall learning experience.

Secondly, this is one of the first studies to use cartoon programme–style animations, complete with characters, dialogues and basic storylines, as instructional tools in higher education. This enables us to investigate which aspect of the design of an animated video contributes most significantly to engaging students’ interest and attention. We find that character design, dialogue scripting and voice acting provide the most potent hooks to engage learner attention and enhance viewer enjoyability. These novel findings inform future educators on the optimal design and production process of animated teaching resources.

Thirdly, we further explore the role of students’ individual and demographic idiosyncrasies, such as age and gender, and how they influence the students’ interactions with the animated videos and the benefits derived from them. Prior studies show that student demographic characteristics, such as gender and age, are significant in determining accounting students’ approaches to learning (Apostolou et al. 2017; Duff 1999). However, no prior studies have investigated whether and how these demographic characteristics affect the students’ learning experience when utilizing animated instructional videos, as measured by the level of interest, enjoyability, ease of understanding and ease of access. The findings in our study provide important insights into how students in various demographic groups derive different benefits from animated teaching resources. Finally, unlike prior studies that report student survey responses (Adam et al. 2017; Mather 2015), we also conduct regression analyses to document findings supported by statistical evidence.

Theories and predictions

We expect animated instructional videos to enhance students’ learning experience in two significant ways. Firstly, under Dewey’s pragmatic view of learning, the learning process is regarded as an inherently social activity derived from human interactions (Chee 2011; Dewey 1916; Kivinen, Piiroinen, and Saikkonen 2016). Consistent with this view, prior studies find that the on-screen appearance of instructors or avatars serves an important social function to engage students (Adams et al. 2014; Cantley, Prendergast, and Schlindwein 2017). Specifically, Wouters, Paas, and Van Merriënboer (2008, p. 667) document that ‘[a]nimated [avatars] can give support to the learner and stimulate the learner to invest effort to understand the model performance depicted in the animation’. Accordingly, we hypothesize that the cartoon characters, dialogues and simulated real-world settings in the animations will enhance students’ learning experience by increasing the level of engagement, interest and enjoyability during the learning process.

Secondly, we expect the visual aids and illustrations to help students attain a better understanding of the concepts and principles explained in the videos. According to cognitive theory, more effective learning occurs when a learner experiences reduced cognitive load during a video viewing, because of the constraint on human working memory capacity (Homer, Plass, and Blake 2008; Mayer 1999). Some debates persist over whether the presence of additional visual content increases or decreases viewers’ cognitive load (Chen and Wu 2015; Homer, Plass, and Blake 2008; Wouters, Paas, and Van Merriënboer 2008), though more recent evidence supports the latter view (Chen and Wu 2015). Accordingly, under cognitive theory, we hypothesize that animated videos will improve the learning outcomes of the viewers and help them attain better understanding.

Method

Study setting

To test these theoretical expectations, we conducted a case study in the context of a compulsory undergraduate final-year accounting course at an Australian university. The course is delivered to over 200 students each semester, who specialize in accountancy as a part of their bachelor degree in business. Some students have dual specializations in combination with corporate finance, management, marketing or international business. A small portion of students undertake their accounting studies in combination with another degree (such as the bachelor of laws, which is the most common). The cohorts of students comprise a balanced mix of male and female students. Given that this is a third-year course, the ages of the students typically range from 20 to 25, consistent with expectation. More specifically, over 84% of the survey respondents reported being between 20 and 23 years of age. Approximately 10% of the survey respondents identified themselves as aged 24–25. Less than 5% of the students reported being 26 or older, and less than 1% 19 or younger.

This study involved the production of a series of animated videos to teach complex concepts and methods of advanced accounting. The animated videos are provided to students as a part of the pre-lecture videos for each topic. Similar to prior studies (e.g. McLaughlin et al. 2014), the animations are distributed on the course online learning platform (Canvas) prior to students attending face-to-face lectures, in order to facilitate a flipped classroom approach (Chen et al. 2014; Kim et al. 2014). After viewing the videos, students complete weekly online quizzes (consisting of four to six questions), which form a part of their summative assessment.

This advanced-level accounting course is characterized by complex, difficult and highly technical content. In past course evaluations, students often commented on the ‘complexity of the topics’, which were ‘difficult to grasp’. One challenge in helping students gain a thorough understanding of the course materials lies in the abstract nature of the convoluted accounting principles, which are difficult to visualize. In addition, given the abundance of technical details and complicated calculations covered in the curriculum, another key challenge is how to engage and motivate students to become interested in the course materials.

Animated teaching videos

In response to these challenges, a series of nine animated cartoon videos were developed and produced, through careful pedagogical design, and deployed over two semesters in the 2017 and 2018 academic years. The animated series covers all major topics in the course. In the syllabus, the animated videos constitute the first teaching resource that students access when studying each topic. The videos are aimed at providing an introductory overview of the topic, explaining the fundamental accounting or business principles and presenting a ‘hook’ to engage students’ interest through real-world examples or story scenarios. Figure 1 provides several screenshots from the animation series. The animations are designed to serve two overarching objectives: the first objective encompasses engaging student attention, enhancing interest in the materials and improving overall enjoyability of the learning process; the second aim is providing visual stimuli to illustrate complex technical concepts to help students achieve better understanding.

Fig 1
Figure 1. Screenshots of animated videos.

Animation technology and production process

The advancement of animation technologies makes the process of creating customized animated videos more accessible to educators. The production process typically involves the following steps. Firstly, the instructor prepares a script and storyboard drawings in accordance with pedagogical needs, and the video producer creates cartoon characters (using Adobe’s Character Animator and Photoshop), animated sets, props and other visual assets from a combination of hand-drawings, computer-generated objects and photographs. Secondly, voice acting is recorded using Character Animator, a software that uses facial-mapping and lip-syncing technology to map a cartoon character’s facial expressions following those of the actor. Voice-overs are recorded separately. Thirdly, the producer edits the visual footage, graphics, background and foregrounds to create a seamless three-dimensional sequence, before adding audio recordings, sound effects, music and captions. Finally, the completed video is exported as an MP4 file and reviewed by the instructor for continuity and accuracy, before it is posted on the course’s online learning platform.

Survey data collection

Two surveys were administered to two different cohorts of students in 2017 and 2018. In each semester, all students participating in this advanced accounting course were invited to fill out the survey, which was administered on the Canvas course website. A total of 109 valid responses were received in the first semester, and 145 were received in the second semester.

The survey instruments were designed to explore students’ experience of engaging with the animated videos. As a part of the survey validation, we conducted a principal components analysis (PCA) to generate the factor loadings for each variable corresponding to each question in the survey instrument. The factor loadings for all questions included in the survey instrument exceeded the validity threshold of 0.40 in the literature (Stevens 1992) (some argue that a lower threshold of 0.35 should have been used given the sample size of 250 [Hair et al. 1998, p. 112]). These results from the PCA supported the validity of the survey instrument. The surveys consisted of three parts: (1) Likert-scale questions relating to different pedagogical features of the animated videos, (2) a free-comment section in response to the question ‘what are the best aspects of the animated (cartoon) videos?’ and (3) questions about students’ individual and demographic information. The survey questions are detailed in Appendix A. The survey administered in the first semester (2017) consisted of fewer Likert questions. Based on the free-response comments provided by the respondents in the first-semester survey, we were able to develop more targeted and detailed Likert-scale questions in the second survey administered in 2018, in order to obtain quantitative evidence to corroborate the qualitative findings from the written free-response comments.

Empirical results

In this section we discuss and analyse the survey results. We first discuss the free-response comments from students, which shed light on the specific aspects of the learning experience that are improved by animated instructional videos. We then provide descriptive statistics relating to the Likert-scale responses. Next, we present the empirical results from a series of regression analyses to provide further insights into the pedagogical benefits of animated videos as a learning tool.

Survey results: Free-response comments

Amongst the 254 survey respondents over two semesters, 173 students (68%) provided written comments in response to the question ‘what are the best aspects of the animated (cartoon) videos?’. The overarching themes identified by students in relation to the best aspects of the animation videos include interesting, engaging, easy (to understand), different, and entertaining. Of 254 survey participants, only 4 students (<2%) provided negative comments about the animated videos (e.g. ‘I don’t care for them’); the remaining comments were positive.

Upon careful review of these written responses, we further grouped the comments into three main categories in accordance with the overarching themes, including (1) comments relating to increased interest, enjoyability and engagement (which measures student attention); (2) comments relating to how animations assist students’ understanding, for example, through simplifying concepts or providing visual illustrations; and (3) comments relating to the attraction of animations as something ‘different’ or a change from conventional teaching materials. The comments from students enabled us to identify a number of recurring themes relating to the animations’ impacts on the learning process. This knowledge in turn allowed us to develop and refine our Likert-scale questions in the second survey to include more targeted questions about the specific pedagogical benefits of the animated videos.

Descriptive statistics

Animated videos and student learning experience

Table 1 reports the student responses to the Likert-scale questions. A total of 254 responses were received over two semesters. Firstly, the survey results provide an overview of the usefulness of the animated videos to students’ learning. In response to Question 11 (‘overall, I find the animated (cartoon) videos helpful to my learning’), 83% of the survey participants either strongly agreed or agreed with this statement.

Table 1. Descriptive statistics of survey responses.
Q# Variable Survey question Responses Strongly disagree Disagree Undecided Agree Strongly agree
1 interesting I find the animated (cartoon) videos interesting to watch. 251 6 2% 14 6% 37 15% 116 46% 78 31%
2 enjoy I enjoy watching the animated (cartoon) videos. 145 1 1% 9 6% 21 14% 55 38% 59 41%
3 engage The animated (cartoon) videos engage my attention and help me concentrate. 142 1 1% 8 6% 25 18% 64 45% 44 31%
4 understand I find the animated (cartoon) videos helpful in assisting my understanding of the key concepts. 251 6 2% 13 5% 34 14% 120 48% 78 31%
5 simplify The animated (cartoon) videos assist my learning by simplifying complex and technical concepts. 145 1 1% 9 6% 18 12% 78 54% 39 27%
6 visual The animated (cartoon) videos enhance my understanding by providing visual stimuli and graphic illustrations of abstract technical concepts. 144 1 1% 10 7% 18 13% 71 49% 44 31%
7 flexible The animated (cartoon) videos provide more flexibility to accommodate my busy schedule (including work commitments). 145 1 1% 11 8% 19 13% 61 42% 53 37%
8 selfpace The animated (cartoon) videos enable me to achieve better outcomes through self-paced learning (e.g. pause, rewind, repeat certain sections). 145 1 1% 10 7% 21 14% 60 41% 53 37%
9 refreshing The animated (cartoon) videos present a refreshing change from regular teaching materials. 143 0 0% 7 5% 14 10% 64 45% 58 41%
10 stimulate The animated (cartoon) videos stimulate my interest in the course materials. 251 4 2% 21 8% 44 18% 109 43% 73 29%
11 animation_overall Overall, I find the animated (cartoon) videos helpful to my learning. 251 4 2% 11 4% 27 11% 136 54% 73 29%
12 more_cartoon I would like to see more animated (cartoon) videos in this course. 107 4 4% 12 11% 22 21% 48 45% 21 20%
13 cartoon_view How much of the animated (cartoon) videos have you watched? (%) 147 9 6% 8 5% 9 6% 24 16% 97 66%
14 lecture_attend How often do you attend lectures in person? (never – always) 254 16 6% 25 10% 58 23% 49 19% 106 42%
18 age Your age 144 1 1% 59 41% 62 43% 15 10% 7 5%
19 cartoon_child How much cartoon/animated programs did you watch in your childhood? 142 2 1% 3 2% 25 18% 61 43% 51 36%
29 cartoon_enjoy How much do you enjoy cartoon and animated programs in general? 145 1 1% 8 6% 17 12% 67 46% 52 36%
        No             Yes
16a voice_acting What do you find to be the most memorable aspect(s) of the animated videos? (Please tick as many as relevant): voice acting, cartoon character design, dialogues, visual cues and graphics, background/set design, music and scoring. 144 No: 88 61%     ---     Yes: 56 39%
16b character_design 144 No: 66 46%     ---     Yes: 78 54%
16c dialogues 144 No: 91 63%     ---     Yes: 53 37%
16d visual_cues 144 No: 71 49%     ---     Yes: 73 51%
16e background_set 144 No: 116 81%     ---     Yes: 28 19%
16f music_scoring 144 No: 128 89%     ---     Yes: 16 11%
17 gender Your gender 141 M: 53 38%     ---     F: 88 62%
18 age_d Your age (median – split) 144 <22: 60 42%     ---     ≥22: 84 58%

In addition, the Likert-scale questions (Q1–Q10) are designed to provide further insights into the specific avenues through which the animations enhance students’ learning experience, including (1) increasing interest, enjoyability and engagement; (2) improving understanding of the technical content; (3) providing flexibility and self-directed learning; and (4) constituting a refreshing change from conventional teaching materials.

Firstly, a vast majority of the survey respondents found the animated videos interesting (Q1: 77% agree/strongly agree), enjoyable (Q2: 79%) and helpful to their concentration (Q3: 76%). Consistently, 72% of the survey participants strongly agreed or agreed that ‘[t]he animated (cartoon) videos [stimulated] my interest in the course materials’ (Q10). Secondly, 79% of the participants agreed or strongly agreed that the animations were ‘helpful in assisting [their] understanding of the key concepts’ (Q4). Similarly, 81% of the participants concurred that the videos ‘[assisted their] learning by simplifying complex and technical concepts’ (Q5), and 80% found that the ‘visual stimuli and graphic illustrations of abstract technical concepts’ enhanced their learning (Q6). Thirdly, a vast majority of survey participants valued the flexibility (Q7: 79% agree/strongly agree) and self-paced learning (Q8: 78% agree/strongly agree) offered by the animated videos. Finally, 86% of the survey participants agreed or strongly agreed that the animations provided ‘a refreshing change from regular teaching materials’ (Q9). These descriptive statistics provide preliminary support for the various pedagogical benefits associated with animated videos; however, in the following sections, we will provide further statistical evidence on the role of each of these factors by conducting regression analyses.

Aspects of animation design and student engagement

The effectiveness of animated teaching resources depends largely on their designs (Lowe 2003). Question 16 of the survey was designed to gauge which specific aspects of the animated videos were most effective in achieving the pedagogical objective of engaging students. The question asked: ‘what do you find to be the most memorable aspect(s) of the animated videos? (Please tick as many as relevant)’, while providing a series of options for multiple selection, including (1) voice acting, (2) character design, (3) dialogues, (4) visual cues and graphics, (5) background or set design and (6) music and scoring. Based on student responses, we computed six binary variables. Each variable was coded 1 if the student had selected the corresponding option and 0 otherwise. As reported in Table 1, character design constituted the most popular aspect of the animation design, with 54% of the survey respondents selecting this option, followed by visual cues and graphics (51%), voice acting (39%), dialogues (37%), background or set design (19%) and music and scoring (11%).

Student demographic characteristics and idiosyncrasies

Moreover, the survey gathered information about the idiosyncratic characteristics of the survey participants, including demographic information such as age and gender, and students’ general attitudes towards cartoons outside the classroom. For example, 62% of the survey participants were female and 38% male; 58% of the students were 22 years of age or older, and 42% were 21 or younger. In response to Question 19, ‘How much cartoon/animated programs did you watch in your childhood?’, 36% reported watching very frequently, 43% often and 18% sometimes, whereas only 2% reported watching occasionally and 1% rarely. We included these questions because prior research evidence shows that leisure activities involving multimedia content can affect its effectiveness for educational purposes (Cilesiz 2009) and impact on students’ learning outcomes (Williams et al. 1982).

Statistical models

Animations and student learning experience

In this study, we employed the following regression models to analyse the survey data. We ran the ordinary least squares models specified in Equations (1) and (2). As robustness tests, we re-estimated the key equations in this study using Tobit regressions and Poisson regressions, in turn. In the untabulated results generated from these additional analyses, the estimated coefficients and statistical significance of the key independent variables remained substantively similar to those reported in the next section. These additional analyses provided further support for the findings in this study.

Animation_overallj = α + β1interestingj | enjoyj | engagej + β2understandj | simplifyj | visualj + β3flexiblej | selfpacej + β4 refreshingj + β5animation_viewj + β6lecture_attendj + β7 cartoon_childj + β8cartoon_enjoyj + β9 agej + β10 genderj + εit (1)

Stimulatej = α + β1interestingj | enjoyj | engagej + β2understandj | simplifyj | visualj β3 flexiblej | selfpacej + β4 refreshingj + β5 animation_viewj + β6 lecture_attendj + β7 cartoon_childj + β8 cartoon_enjoyj + β9 agej + β10 genderj + εit (2)

We assumed that each observation in the analysis (representing each individual student’s survey responses) was independent from other observations, as there was no theoretical or empirical evidence to suggest that students might collaborate on completing the survey or plagiarize each other’s survey responses.

The dependent variable, animation_overallj, represents the overall usefulness of the animation videos to student learning (Q11). In addition, we also ran Equation (2) by employing an alternative dependent variable, stimulatej, which captures the extent to which the animated videos stimulated students’ interest in the course materials (Q10). Each independent variable corresponds to one of the survey questions (Q1–Q9), which explore specific avenues through which animations can impact on the learning process. We grouped the variables into four broad categories: (1) engaging student interest and improving enjoyability of learning (as captured by the variables interestingj, enjoyj and engagej); (2) helping students achieve better understanding by simplifying technical content and providing visual illustrations (understandj, simplifyj and visualj); (3) providing flexibility and facilitating self-paced learning (flexiblej and selfpacej); and (4) offering a refreshing change from the format of conventional teaching material (refreshingj).

Because of the high multicollinearity amongst variables in the same category (e.g. students who found the videos interesting were also likely to find them enjoyable), we ran a series of regression analyses by only including one variable at a time from each category of explanatory variables, while excluding any explanatory variable with a Pearson correlation coefficient of more than 70%. In addition, we report that the variance inflation factor for each regression included in this study was below 7, indicating that multicollinearity is not a significant concern.

Finally, we included the following control variables in the regression models: the amount of animated teaching videos viewed by the student (animation_viewj), the students’ lecture attendance (lecture_attendj), the amount of (non-educational) cartoon programmes the student watched as a child (cartoon_childj), the student’s affinity towards cartoons in general (cartoon_enjoyj) and the student’s age (agej) and gender (genderj).

Aspects of animation design and student engagement

We posit that the usefulness of the animated videos was directly related to the extent to which the animations can engage students. In this section, we explore the specific elements of the animation design that are most important to increasing student interest, enjoyability and engagement. We ran the following two-stage regression models.

Stage 1

interestingj | enjoyj | engagej = α + β1 voice_actingj + β2 character_desionj + β3 dialoguesj + β4 visual_cuesj + β5 background_setj + β6 music_scoringj + εit (3)

Stage 2

Cartoon_overallj = α + β1 interesting_pj | enjoy_pj | engage_pj + β2 cartoon_childj + β3 cartoon_enjoyj + β4 agej + β5 genderj + εit (4)

In the first-stage regression in Equation (3), we used a series of independent variables to capture various aspects of the animation design, including voice acting, character design, dialogues, visual cues and graphics, background and set design, and music and scoring. The three alternative dependent variables (interestingj, enjoyj and engagej) measure the extent of student engagement. In the second-stage regressions, we used the predicted values of interesting, enjoy and engage from the first-stage regressions as independent variables, along with control variables that captured student idiosyncrasies, to predict the overall usefulness of the animations in the learning process.

Regression analysis

Animations and student learning experience

The results from the regressions in Equation (1) are reported in Table 2. Firstly, the estimated coefficient of interestingj is positive and significant in predicting the overall usefulness of animated videos (p < 0.01 and p < 0.05) in Models (1) and (2). This indicates how interesting an animated video was to students and directly relates to its usefulness as an instructional resource. Similarly, in Models (3) and (4), enjoyj is positively and significantly associated with animation_overallj (p < 0.05 or better), which demonstrates that the more students enjoy watching the animations, the more likely they are to find the videos useful to their learning. Consistently, the coefficient of engagej is positive and significant (p < 0.05 and p < 0.10 in Models (5) and (6), respectively), which shows that improved student engagement is a significant predictor of the overall usefulness of the animated videos in the learning process.

Secondly, in Models (7) and (8), the coefficient of the variable understandj is positive and significant in predicting animation_overallj (p < 0.01). These results show that helping students better understand the technical course content constitutes an important pedagogical benefit of the animations. Consistently, in Models (1) through (4) and (6), the variable simplifyj is positive and significant in predicting animation_overallj (p < 0.05 and p < 0.10). Furthermore, the coefficient of visualj is positive (p < 0.01) in Model (9), indicating that ‘providing visual stimuli and graphic illustrations of abstract technical concepts’ serves an important function that significantly determines the overall usefulness of animated instructional videos.

Thirdly, the coefficient of flexiblej is positive and significant (p < 0.01) in Models (1), (3), (5), (7) and (9). Similarly, the coefficient of selfpacej is significant in Models (2), (4) and (6) (p < 0.10). These results show that providing flexibility and enabling self-paced learning also significantly contribute to the usefulness of animated videos.

Finally, the variable refreshingj is consistently positive and significant in Models (1) through (8) in predicting animation_overallj (p < 0.01). This suggests that providing a refreshing change from conventional teaching materials is a significant aspect of the animations that explains their overall usefulness. Amongst the control variables, lecture_attendj is significant in Models (1) through (9) (p < 0.10 or better), suggesting that students who regularly attend lectures, on average, tend to derive greater benefits from animated teaching videos.

Table 2. Animations and student learning experience.
Models Interesting Enjoy Engage Understand Visual
cartoon_ overall cartoon_ overall cartoon_ overall cartoon_ overall cartoon_ overall cartoon_ overall cartoon_ overall cartoon_ overall cartoon_ overall
(1) (2) (3) (4) (5) (6) (7) (8) (9)
interesting 0.206*** 0.211**              
  (0.006) (0.014)              
enjoy     0.146** 0.164***          
      (0.021) (0.009)          
engage         0.155** 0.158*      
          (0.029) (0.056)      
understand             0.346*** 0.396***  
              (0.000) (0.000)  
simplify 0.112* 0.151** 0.123* 0.155** 0.105 0.145*      
  (0.093) (0.031) (0.063) (0.027) (0.162) (0.076)      
visual                 0.399***
                  (0.000)
flexible 0.215***   0.209***   0.226***   0.158***   0.290***
  (0.001)   (0.001)   (0.000)   (0.007)   (0.000)
selfpace   0.146*   0.146*   0.157*   0.075  
    (0.087)   (0.088)   (0.063)   (0.235)  
refreshing 0.335*** 0.345*** 0.373*** 0.375*** 0.360*** 0.369*** 0.333*** 0.348***  
  (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000)  
cartoon_view −0.007 −0.009 −0.009 −0.012 0.002 −0.001 0.001 −0.000 0.044
  (0.758) (0.711) (0.722) (0.630) (0.944) (0.969) (0.981) (0.998) (0.129)
lecture_attend 0.053* 0.055* 0.059* 0.060** 0.061** 0.063** 0.058** 0.059** 0.066**
  (0.066) (0.057) (0.052) (0.043) (0.036) (0.031) (0.025) (0.022) (0.046)
cartoon_child −0.044 −0.049 −0.061 −0.067 −0.057 −0.063 −0.029 −0.025 −0.048
  (0.276) (0.295) (0.191) (0.211) (0.190) (0.215) (0.380) (0.460) (0.313)
cartoon_enjoy 0.043 0.035 0.053 0.045 0.048 0.040 0.023 0.014 0.069
  (0.371) (0.483) (0.283) (0.376) (0.317) (0.423) (0.590) (0.747) (0.220)
age 0.023 0.039 0.015 0.029 0.021 0.038 0.047 0.063 0.042
  (0.579) (0.369) (0.730) (0.529) (0.625) (0.409) (0.255) (0.146) (0.353)
gender −0.068 −0.062 −0.059 −0.055 −0.063 −0.062 −0.043 −0.045 −0.036
  (0.276) (0.338) (0.383) (0.447) (0.352) (0.398) (0.506) (0.508) (0.652)
constant 0.422 0.488* 0.503* 0.580* 0.475* 0.556* 0.440* 0.486* 0.770**
  (0.107) (0.087) (0.097) (0.073) (0.083) (0.067) (0.077) (0.068) (0.028)
N 134 134 135 135 133 133 134 134 136
adj. R2 0.771 0.746 0.760 0.738 0.757 0.730 0.794 0.778 0.657
Notes: All variables are defined in Appendix A.
*p < 0.1, **p < 0.05, ***p < 0.01.

Furthermore, we repeated the analyses by re-estimating the regressions in Equation (2) to predict stimulatej, which captures the extent to which the animated videos stimulated student interest in the course. As reported in Table 3, the estimated coefficients and statistical significance of the key variables remained substantively similar to those reported in Table 2. Specifically, all four aspects of the animations, including interestingj (with enjoyj or engagej as alternatives), understandj (with simplifyj or visualj as alternatives), flexiblej (or selfpacej) and refreshingj remained significant and positive (p < 0.10 or better) in predicting the extent to which the animated videos stimulated student interest in learning the course materials.

Table 3. Animations and student interest in the course materials.
Models Interesting Enjoy Engage Understand Visual
stimulate stimulate stimulate stimulate stimulate stimulate stimulate stimulate stimulate
(1) (2) (3) (4) (5) (6) (7) (8) (9)
interesting 0.352*** 0.338***              
  (0.000) (0.001)              
enjoy     0.373*** 0.378***          
      (0.000) (0.000)          
engage         0.362*** 0.346***      
          (0.001) (0.005)      
understand             0.394*** 0.424***  
              (0.000) (0.000)  
simplify 0.183** 0.226** 0.168** 0.201** 0.133 0.183*      
  (0.023) (0.024) (0.043) (0.043) (0.154) (0.097)      
visual                 0.545***
                  (0.000)
flexible 0.382***   0.350***   0.395***   0.359***   0.392***
  (0.000)   (0.000)   (0.000)   (0.000)   (0.000)
selfpace   0.392***   0.367***   0.397***   0.350***  
    (0.000)   (0.000)   (0.000)   (0.001)  
refreshing 0.173* 0.129 0.184** 0.129 0.167* 0.125 0.266*** 0.233***  
  (0.054) (0.116) (0.039) (0.107) (0.072) (0.156) (0.001) (0.007)  
Controls Yes Yes Yes Yes Yes Yes Yes Yes Yes
Constant Yes Yes Yes Yes Yes Yes Yes Yes Yes
N 135 135 136 136 134 134 135 135 137
adj. R2 0.745 0.733 0.757 0.751 0.738 0.723 0.725 0.711 0.716
Notes: All variables are defined in Appendix A.
*p < 0.1, **p < 0.05, ***p < 0.01.

Aspects of animation design and student engagement

In this section, we estimate a two-stage model as specified in Equations (3) and (4) to further explore which aspects of the animation design contribute most significantly to improving student engagement. Models (1) through (3) of Table 4 report the results from the first-stage regressions. In Model (1), character_designj is the most significant independent variable in predicting how interesting students found the animated videos (interestingj) (p < 0.01), followed by voice_actingj (p < 0.05) and visual_cuesj (p < 0.10). These results provide important insights by demonstrating that character design, voice acting, and visual cues and graphics are the most important features of the animations that make them interesting to students. Consistently, in predicting the enjoyability of animations (enjoyj) in Model (2), character_designj and dialoguesj are both significant (p < 0.05), indicating that characters and dialogues contribute the most to enhance students’ enjoyment of watching the animations. Similarly, in Model (3), character_designj (p < 0.01) and voice_actingj (p < 0.05) remained consistent in predicting student engagement (engagej). Prior studies have explored the use of animated characters in educational videos (Cantley, Prendergast, and Schlindwein 2017; Johnson et al. 2013; Lee, Hsiao, and Ho 2014; Rosenberg-Kima et al. 2010). Consistent with prior evidence that the presence of an animated character increases students’ interest in the subject matter (Johnson et al. 2013), we show that character design is of paramount importance in determining the enjoyability and engagement associated with animated teaching videos.

From these regressions in Equation (1), we calculated predicted values of the first-stage dependent variables, interestingj, enjoyj and engagej, which were then included in the second-stage regressions as explanatory variables. The results from the second-stage regression are reported in Models (4) through (6), Table 4. The coefficients of the predicted variables, interesting_pj, enjoy_pj and engage_pj, are significant and positive in predicting students’ overall rating of their learning experience using the animated videos (p < 0.01). These results further confirmed our expectation that engaging students and increasing students’ interest in and enjoyability in learning constitute a crucial mechanism of improving their overall learning experience through animated videos. Finally, amongst the control variables, cartoon_enjoyj is positive and significant (p < 0.05 or better) in Models (4) through (6), which shows that the more students enjoy (non-educational) cartoon programmes in general, the more they are likely to derive benefits from the animated instructional videos.

Table 4. Two-stage analysis: aspects of animation design and student engagement.
Models Stage 1: student engagement   Stage 2: learning outcomes
interesting enjoy engage cartoon_ overall cartoon_ overall cartoon_ overall
(1) (2) (3) (4) (5) (6)
voice_acting 0.392** 0.134 0.372** interesting_p 0.646***    
  (0.011) (0.382) (0.018)   (0.001)    
character_design 0.482*** 0.342** 0.565*** enjoy_p   0.761***  
  (0.002) (0.036) (0.000)     (0.000)  
dialogues 0.020 0.327** 0.244 engage_p     0.607***
  (0.899) (0.043) (0.114)       (0.000)
visual_cues 0.260* 0.225 0.236 cartoon_child −0.023 −0.030 −0.023
  (0.070) (0.155) (0.114)   (0.786) (0.704) (0.776)
background_set 0.146 0.093 0.149 cartoon_enjoy 0.218** 0.232*** 0.217**
  (0.437) (0.659) (0.417)   (0.013) (0.007) (0.013)
music_scoring 0.080 0.147 −0.121 age 0.051 0.070 0.056
  (0.724) (0.506) (0.485)   (0.471) (0.345) (0.432)
constant 3.429*** 3.619*** 3.328*** gender 0.026 0.021 0.013
  (0.000) (0.000) (0.000)   (0.848) (0.872) (0.919)
        constant 0.591 −0.029 0.755
          (0.503) (0.975) (0.353)
N 143 144 141 N 136 136 136
adj. R2 0.100 0.068 0.137 adj. R2 0.107 0.125 0.118
Notes: All variables are defined in Appendix A.
*p < 0.1, **p < 0.05, ***p < 0.01.

Student demographic characteristics and impacts on learning experience

Students’ individual idiosyncrasies, including demographic characteristics, were expected to play an important role in determining their learning experience (Rosenberg-Kima et al. 2010). In this section, we conduct additional subsample analyses to provide further insights into the way in which student demographic characteristics moderate the relationship between animated teaching videos and learning experience.

Firstly, we re-estimate the regression models in Equation (1) by using two separate subsamples of female versus male students. The results are reported in Panel A, Table 5. In Models (1) through (4), we estimated the regressions over the subsample of only female students. The variables interestingj and understandj are significant in predicting the overall usefulness of animated videos (p < 0.01 and p < 0.05). We then re-estimate the regressions using the subsample of male students, as reported in Models (5) through (8). In contrast, neither interestingj nor understandj is consistently significant; instead the coefficient of simplifyj is positive and significant (p < 0.05) in predicting animated_overallj. These results provide important novel insights into how male and female students can derive different benefits from the animated teaching videos. While female students valued the fact that animated videos made learning more interesting and helped improve students’ self-assessed understanding of the technical content, male students placed more emphasis on the benefit of animations in simplifying complex technical principles to assist them in their learning process.

Table 5. Student demographic characteristics and impacts on learning experience. Panel A. Student gender and benefits of animated videos
Models Female students Male students
cartoon_ overall cartoon_ overall cartoon_ overall cartoon_ overall cartoon_ overall cartoon_ overall cartoon_ overall cartoon_ overall
(1) (2) (3) (4) (5) (6) (7) (8)
interesting 0.229*** 0.214**     0.228 0.246    
  (0.005) (0.023)     (0.118) (0.144)    
understand     0.359*** 0.388***     0.268 0.318*
      (0.000) (0.000)     (0.126) (0.064)
simplify 0.111 0.154**     0.217** 0.230**    
  (0.133) (0.030)     (0.046) (0.041)    
flexible 0.181**   0.124*   0.216**   0.199*  
  (0.011)   (0.054)   (0.045)   (0.088)  
selfpace   0.155   0.082   0.152   0.102
    (0.153)   (0.277)   (0.277)   (0.426)
refreshing 0.361*** 0.380*** 0.349*** 0.370*** 0.200 0.185 0.370*** 0.368**
  (0.000) (0.000) (0.000) (0.000) (0.143) (0.373) (0.008) (0.030)
Controls Yes Yes Yes Yes Yes Yes Yes Yes
Constant Yes Yes Yes Yes Yes Yes Yes Yes
N 82 82 83 83 52 52 51 51
adj. R2 0.774 0.761 0.818 0.809 0.790 0.769 0.768 0.748
interesting 0.187* 0.132     0.251** 0.306***    
  (0.076) (0.284)     (0.016) (0.002)    
understand     0.261*** 0.247**     0.462*** 0.527***
      (0.003) (0.011)     (0.000) (0.000)
simplify 0.108 0.141     0.127 0.171*    
  (0.207) (0.100)     (0.218) (0.091)    
flexible 0.217***   0.173**   0.177   0.137  
  (0.005)   (0.031)   (0.142)   (0.100)  
selfpace   0.265***   0.198*   0.011   0.001
    (0.007)   (0.056)   (0.931)   (0.990)
refreshing 0.367*** 0.359*** 0.415*** 0.407*** 0.296*** 0.366*** 0.242*** 0.306***
  (0.001) (0.001) (0.000) (0.000) (0.004) (0.004) (0.006) (0.001)
Controls Yes Yes Yes Yes Yes Yes Yes Yes
Constant Yes Yes Yes Yes Yes Yes Yes Yes
N 80 80 79 79 54 54 55 55
adj. R2 0.715 0.711 0.718 0.711 0.827 0.811 0.872 0.862
Notes: All variables are defined in Appendix A.
*p < 0.1, **p < 0.05, ***p < 0.01.

Secondly, we also conducted similar subsample analyses using student age. We divided the observations into two groups by the sample median age (22 years old): one group consisted of older students (22 years of age or older), and the other consisted of younger students (21 years of age or younger). We re-estimated the regressions in Equation (1) using each subsample, and we report the results in Panel B, Table 5. As reported in Models (1) through (4), within the subsample of older students, understandj is significant in predicting animated_overallj (p < 0.01 and p < 0.05 in Models (3) and (4), respectively), in addition to flexiblej (p < 0.05 or better) and selfpacej (p < 0.10 or better). These results demonstrate that, for older students, the key benefits of animated videos lie in helping them attain better understanding of the technical content and facilitating flexible and self-paced learning. In contrast, when the regressions were re-estimated using the subsample of younger students, as reported in Models (5) through (8), flexible and selfpacej are no longer significant. While understandj is consistently significant (p < 0.01), interestingj is also a significant predictor of animation_overallj (p < 0.05 and p < 0.01 in Models (5) and (6), respectively).

These results show that younger and older students derive benefits from animated videos for vastly different reasons. To younger students, making learning more interesting is an important aspect of interacting with animated videos. In contrast, older students, who are more likely to be self-motivated and career-conscious, do not place as much importance on being engaged; rather, they value having access to resources that facilitate flexible and self-paced learning. Another reason that can explain the importance of flexibility to older students is that they are more likely to have work commitments alongside their studies; consequently, this cohort of students prefers teaching resources that can enable them to engage in self-directed learning.

Conclusion

Key findings and implications

This study explores the use of animated videos in higher education, specifically to teach complex technical content in an advanced-level undergraduate accounting course. This is the first study that utilized a series of animations to serve the dual pedagogical objectives of explaining complex concepts and principles to improve students’ understanding, while engaging students’ interest and attention with dialogues, humour and real-world examples. Overall, the findings in this study provide numerous novel and valuable insights in relation to the use of animations in higher education.

Firstly, free-response survey comments and regression results both showed that animated teaching videos can enhance students’ learning experience through four specific avenues, including (1) increasing student interest and engagement in the learning process, (2) improving students’ self-assessed understanding of the materials by simplifying the technical concepts and providing visual aids, (3) facilitating flexible and self-paced learning and (4) providing a refreshing change from conventional teaching materials. We note that students’ self-assessed level of understanding is commonly used as an empirical proxy for the level of understanding (e.g. Daigle, Hayes, and Morris 2014; Mather 2015; Richardson and Louwers 2010). These findings shed light on the multifaceted pedagogical benefits of using animated instructional videos in teaching complex materials.

Secondly, we explored the specific aspects of animation design that contribute to enhancing student engagement. Statistical evidence showed that character design, dialogues and voice acting in the animations constitute the most vital elements that explain students’ interest, enjoyability and engagement during the learning process. These results provide valuable insights to inform future educators in relation to the design and production of animated resources.

Thirdly, this study provided important insights into the role of student idiosyncrasies in influencing their learning experience. The results showed that animated videos assist different student cohorts in significantly different ways. While all cohorts of students (regardless of gender and age) found animations useful for assisting their understanding of the technical content, female and younger students in particular valued the fact that animations make learning more interesting. To male students, a significant source of value added by animations lay in simplifying complex technical concepts. Finally, older students appreciated the flexibility provided by the animated teaching videos to enable self-directed learning. These findings contribute new insights into the pedagogical value of animations by informing future educators that, in designing effective animated teaching resources, one size does not fit all.

Limitations and directions for future research

There are several limitations to this study. Firstly, this study was conducted in the setting of an undergraduate course at an Australian university. This limits the generalizability of the findings, as they may not necessarily be extrapolated to other country settings, student cohorts, cultural backgrounds or year levels. Secondly, this study explored a variety of pedagogical benefits associated with the use of animated teaching videos. While some of these benefits as perceived by students (such as providing a refreshing change to conventional teaching resources) are unique to animated videos, other benefits (such as providing flexibility in learning) potentially apply to all recorded multimedia resources (whether animated or not). Thirdly, the empirical evidence in this study is based on self-reported responses from survey participants, rather than metrics derived from objective assessments. Further studies would be required to provide statistical evidence on the impacts of animated videos on the actual level of understanding, by adopting experimental or treatment-/control-group-based research methodologies. Finally, new technologies and pedagogical innovations are not costless. The design, development and production of animated videos require considerable resources. This study did not provide a direct cost–benefit analysis, as it lacks financial data on the direct and overhead costs associated with producing the animations, nor did it quantify the pedagogical benefits associated with animated videos in dollar value, as such quantification would be difficult if not impossible. Notwithstanding these limitations, this study documents evidence of improved student learning experience associated with an underexplored area of pedagogical innovation and offers novel insights and guidance to future educators to assist them in the process of producing animated resources.

Future studies may explore other aspects of students’ demographic characteristics, such as cultural backgrounds or language capabilities (e.g. English as a first or additional language). In addition, while this study examined the use of animated instructional videos in the field of business education, adding to existing evidence from medical and science educators (e.g. Adam et al. 2017; Kelly and Jones 2007), animations also offer significant potential value to educators in other disciplines. Specifically, animated videos can be used not only as instructional tools to teach new concepts, but also to present case studies for students to apply and utilize their knowledge. Animated case studies can be particularly relevant to disciplines that require scenario-based learning, such as law, business and medicine (e.g. Adam et al. 2017). For example, legal educators can potentially derive significant pedagogical benefits by creating animations to bring to life vivid case scenarios for demonstration, problem discussion and assessment purposes. Furthermore, researchers can delve deeper into understanding the impacts of animations on students’ learning experience from a psychological perspective, such as how they influence students’ motivation and emotional commitment to learning, which may provide fruitful areas of future research.

Acknowledgements

The authors thank two anonymous reviewers and participants at the 2017 Festival of Learning and Teaching at the University of Adelaide for their helpful comments. The authors gratefully acknowledge financial support from the 2017 Course Development Grant provided by the Faculty of the Professions, University of Adelaide.

References

Abdul Jabbar, A. I. & Felicia, P. (2015) ‘Gameplay engagement and learning in game-based learning: a systematic review’, Review of Educational Research, vol. 85, no. 4, pp. 740–779. doi: 10.3102/0034654315577210.

Adam, M., et al., (2017) ‘The use of short, animated, patient-centered springboard videos to underscore the clinical relevance of preclinical medical student education’, Academic Medicine, vol. 92, no. 7, pp. 961–965. doi: 10.1097/ACM.0000000000001574.

Adams, C., et al., (2014) ‘A phenomenology of learning large: the tutorial sphere of xMOOC video lectures’, Distance Education, vol. 35, no. 2, pp. 202–216. doi: 10.1080/01587919.2014.917701.

Anderson, A., et al., (2018) ‘A comparison of video modelling techniques to enhance social-communication skills of elementary school children’, International Journal of Educational Research, vol. 87, pp. 100–109. doi: https://doi.org/10.1016/j.ijer.2016.05.016.

Apostolou, B., et al., (2017) ‘Analysis of trends in the accounting education literature (1997–2016)’, Journal of Accounting Education, vol. 41, pp. 1–14. doi: https://doi.org/10.1016/j.jaccedu.2017.09.003.

Baron, C. (2016) ‘Using embedded visual coding to support contextualization of historical texts’, American Educational Research Journal, vol. 53, no. 3, pp. 516–540. doi: 10.3102/0002831216637347.

Bassford, M. L., et al., (2016) ‘Crashed – a live immersive, learning experience embedding stem subjects in a realistic, interactive crime scene’, Research in Learning Technology, vol. 24, p. 30089. doi: http://dx.doi.org/10.3402/rlt.v24.30089.

Cantley, I., Prendergast, M. & Schlindwein, F. (2017) ‘Collaborative cognitive-activation strategies as an emancipatory force in promoting girls’ interest in and enjoyment of mathematics: a cross-national case study’, International Journal of Educational Research, vol. 81, pp. 38–51. doi: https://doi.org/10.1016/j.ijer.2016.11.004.

Chan, S. H., et al., (2016) ‘Using an educational computer program to enhance student performance in financial accounting’, Journal of Accounting Education, vol. 36, pp. 43–64. doi: https://doi.org/10.1016/j.jaccedu.2016.05.001.

Chee, Y. S. (2011) ‘Learning as becoming through performance, play, and dialog: a model of game-based learning with the game legends of alkhimia’, Digital Culture & Education, vol. 3, pp. 98–122.

Chen, C.-M. & Wu, C.-H. (2015) ‘Effects of different video lecture types on sustained attention, emotion, cognitive load, and learning performance’, Computers & Education, vol. 80, pp. 108–121. doi: https://doi.org/10.1016/j.compedu.2014.08.015.

Chen, Y., Wang, Y., Kinshuk & Chen, N.-S. (2014) ‘Is flip enough? Or should we use the flipped model instead?’, Computers & Education, vol. 79, pp. 16–27. doi: https://doi.org/10.1016/j.compedu.2014.07.004.

Chiou, C.-C., Tien, L.-C. & Lee, L.-T. (2015) ‘Effects on learning of multimedia animation combined with multidimensional concept maps’, Computers & Education, vol. 80, pp. 211–223. doi: https://doi.org/10.1016/j.compedu.2014.09.002.

Cilesiz, S. (2009) ‘Educational computer use in leisure contexts: a phenomenological study of adolescents’ experiences at internet cafés’, American Educational Research Journal, vol. 46, no. 1, pp. 232–274. doi: 10.3102/0002831208323938.

Clark, D. B., Tanner-Smith, E. E. & Killingsworth, S. S. (2016) ‘Digital games, design, and learning: a systematic review and meta-analysis’, Review of Educational Research, vol. 86, no. 1, pp. 79–122. doi: 10.3102/0034654315582065.

Crook, C. (2012) ‘The ‘digital native’ in context: tensions associated with importing web 2.0 practices into the school setting’, Oxford Review of Education, vol. 38, no. 1, pp. 63–80. doi: 10.1080/03054985.2011.577946.

Daigle, R. J., Hayes, D. C. & Morris, P. W. (2014) ‘Helping students understand occupational fraud by applying the ACFE report to daytime television talk show confessions’, Issues in Accounting Education, vol. 29, no. 2, pp. 319–330. doi: 10.2308/iace-50545.

Dewey, J. (1916) Democracy and education, Southern Illinois University Press, Carbondale and Edwardsville.

Duff, A. (1999) ‘Access policy and approaches to learning’, Accounting Education, vol. 8, no. 2, pp. 99–110. doi: 10.1080/096392899330955.

Ellis, T. (2004) ‘Animating to build higher cognitive understanding: a model for studying multimedia effectiveness in education’, Journal of Engineering Education, vol. 93, no. 1, pp. 59–64. doi: https://doi.org/10.1002/j.2168-9830.2004.tb00788.x.

Eysink, T. H. S., et al., (2009) ‘Learner performance in multimedia learning arrangements: an analysis across instructional approaches’, American Educational Research Journal, vol. 46, no. 4, pp. 1107–1149. doi: 10.3102/0002831209340235.

Friesen, N. (2011) ‘The lecture as a transmedial pedagogical form: a historical analysis’, Educational Researcher, vol. 40, no. 3, pp. 95–102. doi: 10.3102/0013189X11404603.

Furlong, J. & Davies, C. (2012) ‘Young people, new technologies and learning at home: taking context seriously’, Oxford Review of Education, vol. 38, no. 1, pp. 45–62. doi: 10.1080/03054985.2011.577944.

Gerjets, P. H. & Hesse, F. W. (2004) ‘When are powerful learning environments effective? The role of learner activities and of students’ conceptions of educational technology’, International Journal of Educational Research, vol. 41, no. 6, pp. 445–465. doi: https://doi.org/10.1016/j.ijer.2005.08.011.

Goldman, R. (2004) ‘Video perspectivity meets wild and crazy teens: a design ethnography’, Cambridge Journal of Education, vol. 34, no. 2, pp. 157–178. doi: 10.1080/03057640410001700543.

Gorissen, P., Van Bruggen, J. & Jochems, W. (2012) ‘Students and recorded lectures: survey on current use and demands for higher education’, Research in Learning Technology, vol. 20, no. 3, pp. 297–311. doi: 10.3402/rlt.v20i0.17299.

Greenhow, C., Robelia, B. & Hughes, J. E. (2009) ‘Learning, teaching, and scholarship in a digital age: web 2.0 and classroom research: what path should we take now?’, Educational Researcher, vol. 38, no. 4, pp. 246–259. doi: 10.3102/0013189X09336671.

Hair, J. F., et al., (1998) Multivariate Data Analysis, 5th edn, Prentice-Hall, London.

Holtzblatt, M. & Tschakert, N. (2011) ‘Expanding your accounting classroom with digital video technology’, Journal of Accounting Education, vol. 29, no. 2, pp. 100–121. doi: https://doi.org/10.1016/j.jaccedu.2011.10.003.

Homer, B. D., Plass, J. L. & Blake, L. (2008) ‘The effects of video on cognitive load and social presence in multimedia-learning’, Computers in Human Behavior, vol. 24, no. 3, pp. 786–797. doi: https://doi.org/10.1016/j.chb.2007.02.009.

Johnson, A. M., et al., (2013) ‘Pedagogical agent signaling of multiple visual engineering representations: the case of the young female agent’, Journal of Engineering Education, vol. 102, no. 2, pp. 319–337. doi: 10.1002/jee.20009.

Johnson, B. G., Phillips, F. & Chase, L. G. (2009) ‘An intelligent tutoring system for the accounting cycle: enhancing textbook homework with artificial intelligence’, Journal of Accounting Education, vol. 27, no. 1, pp. 30–39. doi: https://doi.org/10.1016/j.jaccedu.2009.05.001.

Jordan, L. (2012) ‘Video for peer feedback and reflection: embedding mainstream engagement into learning and teaching practice’, Research in Learning Technology, vol. 20, pp. 16–25. doi: 10.3402/rlt.v20i0.19192.

Kaufmann, P. B. & Mohan, J. (2009) Video Use and Higher Education: Options for the Future, Report for Intelligent Television/Copyright Clearance Center/New York University, New York.

Kelly, R. M. & Jones, L. L. (2007) ‘Exploring how different features of animations of sodium chloride dissolution affect students’ explanations’, Journal of Science Education and Technology, vol. 16, no. 5, pp. 413–429. doi: 10.1007/s10956-007-9065-3.

Keogh, B. & Naylor, S. (1999) ‘Concept cartoons, teaching and learning in science: an evaluation’, International Journal of Science Education, vol. 21, no. 4, pp. 431–446. doi: 10.1080/095006999290642.

Kim, M. K., et al., (2014) ‘The experience of three flipped classrooms in an urban university: an exploration of design principles’, The Internet and Higher Education, vol. 22, pp. 37–50. doi: https://doi.org/10.1016/j.iheduc.2014.04.003.

Kinder, J. S. (1942) ‘Chapter viii: visual aids in education’, Review of Educational Research, vol. 12, no. 3, pp. 336–344. doi: 10.3102/00346543012003336.

Kivinen, O., Piiroinen, T. & Saikkonen, L. (2016) ‘Two viewpoints on the challenges of ICT in education: knowledge-building theory vs. A pragmatist conception of learning in social action’, Oxford Review of Education, vol. 42, no. 4, pp. 377–390. doi: 10.1080/03054985.2016.1194263.

Lee, Y.-H., Hsiao, C. & Ho, C.-H. (2014) ‘The effects of various multimedia instructional materials on students’ learning responses and outcomes: a comparative experimental study’, Computers in Human Behavior, vol. 40, pp. 119–132. doi: https://doi.org/10.1016/j.chb.2014.07.041.

Lento, C. (2017) ‘Incorporating whiteboard voice-over video technology into the accounting curriculum’, Issues in Accounting Education, vol. 32, no. 3, pp. 153–168. doi: 10.2308/iace-51584.

Loong, E. Y.-K. & Herbert, S. (2012) ‘Student perspectives of web-based mathematics’, International Journal of Educational Research, vol. 53, pp. 117–126. doi: https://doi.org/10.1016/j.ijer.2012.03.002.

Lowe, R. K. (1999) ‘Extracting information from an animation during complex visual learning’, European Journal of Psychology of Education, vol. 14, pp. 225–244.

Lowe, R. K. (2003) ‘Animation and learning: selective processing of information in dynamic graphics’, Learning and Instruction, vol. 13, no. 2, pp. 157–176. doi: https://doi.org/10.1016/S0959-4752(02)00018-X.

Lyons, A., Reysen, S. & Pierce, L. (2012) ‘Video lecture format, student technological efficacy, and social presence in online courses’, Computers in Human Behavior, vol. 28, no. 1, pp. 181–186. doi: https://doi.org/10.1016/j.chb.2011.08.025.

Mather, R. (2015) ‘A mixed-methods exploration of an environment for learning computer programming’, Research in Learning Technology, vol. 23, pp. 1–19. doi: 10.3402/rlt.v23.27179.

Mayer, R. E. (1999) ‘Multimedia aids to problem-solving transfer’, International Journal of Educational Research, vol. 31, no. 7, pp. 611–623. doi: https://doi.org/10.1016/S0883-0355(99)00027-0.

Mayer, R. E. & Anderson, R. (1992) ‘The instructive animation: helping students build connections between words and pictures in multimedia learning’, Journal of Educational Psychology, vol. 84, no. 4, pp. 444–452. doi: 10.1037/0022-0663.84.4.444.

McLaughlin, J. E., et al., (2014) ‘The flipped classroom: a course redesign to foster learning and engagement in a health professions school’, Academic Medicine, vol. 89, no. 2, pp. 236–243.

Nelson, K. G., et al., (2017) ‘Students’ misconceptions about semiconductors and use of knowledge in simulations’, Journal of Engineering Education, vol. 106, no. 2, pp. 218–244. doi: 10.1002/jee.20163.

Pincus, K. V., et al., (2017) ‘Forces for change in higher education and implications for the accounting academy’, Journal of Accounting Education, vol. 40, pp. 1–18. doi: https://doi.org/10.1016/j.jaccedu.2017.06.001.

Rebele, J. E. & St. Pierre, E. K. (2015) ‘Stagnation in accounting education research’, Journal of Accounting Education, vol. 33, no. 2, pp. 128–137. doi: https://doi.org/10.1016/j.jaccedu.2015.04.003.

Richardson, R. C. & Louwers, T. J. (2010) ‘Using computerized audit software to learn statistical sampling: an instructional resource’, Issues in Accounting Education, vol. 25, no. 3, pp. 553–567. doi: 10.2308/iace.2010.25.3.553.

Ronchetti, M. (2010) ‘Using video lectures to make teaching more interactive’, International Journal of Emerging Technologies in Learning, vol. 5, no. 2, pp. 45–48.

Roschelle, J. & Pea, R. (1999) ‘Trajectories from today’s www to a powerful educational infrastructure’, Educational Researcher, vol. 28, no. 5, pp. 22–43. doi: 10.3102/0013189X028005022.

Roschelle, J., et al., (2010) ‘Integration of technology, curriculum, and professional development for advancing middle school mathematics:Three large-scale studies’, American Educational Research Journal, vol. 47, no. 4, pp. 833–878. doi: 10.3102/0002831210367426.

Rosenberg-Kima, R. B., et al., (2010) ‘The influence of computer-based model’s race and gender on female students’ attitudes and beliefs towards engineering’, Journal of Engineering Education, vol. 99, no. 1, pp. 35–44.

Sanger, M. J., Brecheisen, D. M. & Hynek, B. M. (2001) ‘Can computer animations affect college biology students’ conceptions about diffusion & osmosis?’, The American Biology Teacher, vol. 63, no. 2, pp. 104–109. doi: 10.2307/4451051.

Spencer, R. C. (1938) ‘The use of illustrative materials’, The Journal of Higher Education, vol. 9, no. 4, pp. 207–216. doi: 10.1080/00221546.1938.11779674.

Sproull, N. (1973) ‘Visual attention, modeling behaviors, and other verbal and nonverbal meta-communication of prekindergarten children viewing sesame street’, American Educational Research Journal, vol. 10, no. 2, pp. 101–114. doi: 10.3102/00028312010002101.

Squire, K. (2006) ‘From content to context: videogames as designed experience’, Educational Researcher, vol. 35, no. 8, pp. 19–29. doi: 10.3102/0013189x035008019.

Stevens, J. P. (1992) Applied multivariate statistics for the social sciences, 2nd edn, Erlbaum, Hillsdale, NJ.

Sun, P.-C. & Cheng, H. K. (2007) ‘The design of instructional multimedia in e-learning: a media richness theory-based approach’, Computers & Education, vol. 49, no. 3, pp. 662–676. doi: https://doi.org/10.1016/j.compedu.2005.11.016.

Svenson, E. V. & Sheats, P. H. (1950) ‘Chapter vi: audio-visual aids in adult education’, Review of Educational Research, vol. 20, no. 3, pp. 216–223. doi: 10.3102/00346543020003216.

Takacs, Z. K., Swart, E. K. & Bus, A. G. (2015) ‘Benefits and pitfalls of multimedia and interactive features in technology-enhanced storybooks: a meta-analysis’, Review of Educational Research, vol. 85, no. 4, pp. 698–739. doi: 10.3102/0034654314566989.

Tan, E. & Pearce, N. (2011) ‘Open education videos in the classroom: exploring the opportunities and barriers to the use of YouTube in teaching introductory sociology’, Research in Learning Technology, vol. 19, pp. 125–133. doi: 10.3402/rlt.v19s1/7783.

Tasker, R. & Dalton, R. (2008) ‘Visualizing the molecular world – design, evaluation, and use of animations’, in Visualization: Theory and Practice in Science Education, eds J. K. Gilbert, M. Reiner & M. Nakhleh, Springer, Dordrecht, Netherlands, pp. 103–131.

Taylor, T. (2012) ‘Preparing the foundations for video-based practice-placement support: establishing the role from a students’ perspective’, Research in Learning Technology, vol. 20, pp. 71–84. doi: 10.3402/rlt.v20i0.19193.

Theobald, M. (2017) ‘Children as research participants in educational research using video-stimulated accounts’, International Journal of Educational Research, vol. 86, pp. 131–143. doi: https://doi.org/10.1016/j.ijer.2017.07.008.

Trifonas, P. (2001) ‘Simulations of culture: Disney and the crafting of American popular culture’, Educational Researcher, vol. 30, no. 1, pp. 23–28. doi: 10.3102/0013189X030001023.

Voithofer, R. (2005) ‘Designing new media education research: the materiality of data, representation, and dissemination’, Educational Researcher, vol. 34, no. 9, pp. 3–14. doi: 10.3102/0013189X034009003.

Warwick, P. & Stephenson, P. (2002) ‘Reconstructing science in education: insights and strategies for making it more meaningful’, Cambridge Journal of Education, vol. 32, no. 2, pp. 143–151. doi: 10.1080/03057640220147513.

Watty, K., McKay, J. & Ngo, L. (2016) ‘Innovators or inhibitors? Accounting faculty resistance to new educational technologies in higher education’, Journal of Accounting Education, vol. 36, pp. 1–15. doi: https://doi.org/10.1016/j.jaccedu.2016.03.003.

Wendt, P. R. & Butts, G. K. (1962) ‘Chapter iii: audiovisual materials’, Review of Educational Research, vol. 32, no. 2, pp. 141–155. doi: 10.3102/00346543032002141.

Williams, P. A., et al., (1982) ‘The impact of leisure-time television on school learning: a research synthesis’, American Educational Research Journal, vol. 19, no. 1, pp. 19–50. doi: 10.3102/00028312019001019.

Wouters, P., Paas, F. & Van Merriënboer, J. J. G. (2008) ‘How to optimize learning from animated models: a review of guidelines based on cognitive load’, Review of Educational Research, vol. 78, no. 3, pp. 645–675. doi: 10.3102/0034654308320320.

Appendices

Appendix A. Survey instrument.

No. Questions Semester(s) Variable Likert or other format
1 I find the animated (cartoon) videos interesting to watch. both interesting 1 2 3 4 5
2 I enjoy watching the animated (cartoon) videos. 2nd Sem enjoy 1 2 3 4 5
3 The animated (cartoon) videos engage my attention and help me concentrate. 2nd Sem engage 1 2 3 4 5
4 I find the animated (cartoon) videos helpful in assisting my understanding of the key concepts. both understand 1 2 3 4 5
5 The animated (cartoon) videos assist my learning by simplifying complex and technical concepts. 2nd Sem simplify 1 2 3 4 5
6 The animated (cartoon) videos enhance my understanding by providing visual stimuli and graphic illustrations of abstract technical concepts. 2nd Sem visual 1 2 3 4 5
7 The animated (cartoon) videos provide more flexibility to accommodate my busy schedule (including work commitments). 2nd Sem flexible 1 2 3 4 5
8 The animated (cartoon) videos enable me to achieve better outcomes through self-paced learning (e.g. pause, rewind, repeat certain sections). 2nd Sem selfpace 1 2 3 4 5
9 The animated (cartoon) videos present a refreshing change from regular teaching materials. 2nd Sem refreshing 1 2 3 4 5
10 The animated (cartoon) videos stimulate my interest in the course materials. both stimulate 1 2 3 4 5
11 Overall, I find the animated (cartoon) videos helpful to my learning. both animation_overall 1 2 3 4 5
12 I would like to see more animated (cartoon) videos in this course. 1st Sem -- 1 2 3 4 5
13 How much of the animated (cartoon) videos have you watched? (%) 2nd Sem cartoon_watch <49 50–64 65–74 75–84 >85%
14 How often do you attend lectures in person? (%) both lecture_attend <49 50–64 65–74 75–84 >85%
15 What are the best aspects of the animated (cartoon) videos? both -- Free response
16 What do you find to be the most memorable aspect(s) of the animated videos? (Please tick as many as relevant): voice acting, cartoon character design, dialogues, visual cues and graphics, background/set design, music and scoring. 2nd Sem voice_acting; character_design; dialogues; visual_cues; background_design; music_scoring Multiple selection
  Please tell us a little about yourself:      
17 Your gender 2nd Sem gender F M I’d rather not say
18 Your age 2nd Sem age <19 20–21 22–23 24–25 >25
19 How much cartoon/animated programs did you watch in your childhood? 2nd Sem cartoon_child 1* 2* 3* 4* 5*
20 How much do you enjoy cartoon and animated programs in general? 2nd Sem cartoon_enjoy 1^ 2^ 3^ 4^ 5^

Legend

Likert scale (Questions 1–12) 1
Strongly disagree
2
Disagree
3
Undecided
4
Agree
5
Strongly Agree
Likert scale* (Question 19) 1*
Rarely
2*
Occasionally
3*
Sometimes
4*
Often
5*
Very frequently
Likert scale^ (Question 20) 1^
I dislike cartoons in general
2^
Not much
3^
Indifferent
4^
Reasonably well
5^
Very much