A model for designing hypervideo-based instructional ...

Interactive Learning Environments

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A model for designing hypervideo-based instructional scenarios Alberto A. P. Cattaneo, Hans van der Meij, Carmela Aprea, Florinda Sauli & Carmen Zahn To cite this article: Alberto A. P. Cattaneo, Hans van der Meij, Carmela Aprea, Florinda Sauli & Carmen Zahn (2018): A model for designing hypervideo-based instructional scenarios, Interactive Learning Environments, DOI: 10.1080/10494820.2018.1486860 To link to this article: https://doi.org/10.1080/10494820.2018.1486860

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INTERACTIVE LEARNING ENVIRONMENTS https://doi.org/10.1080/10494820.2018.1486860

A model for designing hypervideo-based instructional scenarios Alberto A. P. Cattaneoa, Hans van der Meijb, Carmela Apreac*, Florinda Saulia and Carmen Zahnd a

Research and Development Department, Swiss Federal Institute for Vocational Education and Training, Lugano, Switzerland; bFaculty of Behavioural, Management and Social Sciences, Department of Educational Science and Technology, University of Twente, Enschede, the Netherlands; cSchool of Economics and Business Administration, Friedrich-Schiller-University Jena, Jena, Germany; dSchool of Applied Psychology, University of Applied Sciences and Arts Northwestern Switzerland, Olten, Switzerland ABSTRACT

ARTICLE HISTORY

In this article, we provide a conceptual model for the design of instructional scenarios integrating hypervideo as an instructional tool. The model provides a structural aid for making design decisions about using hypervideo in instruction. We start by introducing the theoretical rationale for hypervideo as a tool, exploiting three different interactivity functions. We then examine the cognitive and socio-cognitive theories that can inform the design and usage of hypervideo. Next, we present the instantiation of these functions and theories in a software interface, after which we present the model, which is based on the following two layers of design decisions: the first pertains to the interactivity features and the second is connected with the instructional strategy. Three main design steps are presented in the form of guidelines, corresponding to a preparation phase, a production phase, and a use phase. Finally, a set of cases exhibiting exemplary implementations of a hypervideo-based instructional scenario are described.

Received 9 February 2017 Accepted 6 June 2018 KEYWORDS

Interactive video; hypervideo; instructional design; learning scenario; vocational education

Introduction Videos are one of the most recurrent media used both for leisure and teaching and learning activities. Usage statistics from YouTube report a staggering billion unique users visiting its website, over six billion hours of video viewed each month, and 100 hours of video uploaded every minute (YouTube, 2015). The data are a ready-made indicator of the capillary diffusion of video in everyday life. In school, video has become very popular as well. Video was already reported to be the mostused medium in schools ten years ago (Corporation for Public Broadcasting, 2004; Feierabend & Rathgeb, 2008, 2009). Since then, its popularity in education has only grown, as illustrated by video’s prominent role in Massive Open Online Courses (MOOCs) (inter alia Giannakos, Jaccheri, & Krogstie, 2014). In sum, teachers and learners alike appear to have embraced video as a preferred instructional medium. Although it is hardly disputed that video can contribute to learning, it has proven surprisingly difficult to establish its superiority compared to, for example, combinations of static representations of text and pictures. Researchers are still hard pressed to create equivalent conditions for static and dynamic representations in content or procedures. For instance, mixed findings for the effects of animations on learning prompted Ploetzner and Lowe (2012) to take a step back and analyze the CONTACT Alberto A. P. Cattaneo alberto.cattaneo@sfivet.swiss *Present address: Business and Economic Education – Instructional Systems Design and Evaluation, Business School, University of Mannheim, Mannheim, Germany. © 2018 Informa UK Limited, trading as Taylor & Francis Group

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designs of 44 empirical studies in an effort to find an overarching theoretical framework. Thus, it is not surprising that the scientific results on the general effectiveness of video for learning are still inconsistent (e.g. Merkt, Weigand, Heier, & Schwan, 2011). Technology, of course, will not wait for researchers to solve their effectiveness issues; rather, it has progressed and given rise to new technologies, including “hypervideo”. Hypervideo was designed to overcome some disadvantages of video, such as limited opportunities for interaction, reflection, and annotation (Chambel, Zahn, & Finke, 2004). This paper focuses on hypervideo’s contribution to learning and teaching. The paper pursues the following two goals: The first goal is to explore the theoretical bases for hypervideo. This venture brought us to consider the issue of interactivity, which we consider the most distinguishing feature. As we analyzed existing hypervideo programs’ affordances for interactivity, we discovered that such programs often failed to fully exploit all possibilities that would arise from a perspective on hypervideo as a learning tool within the same software. This prompted us to design a new hypervideo tool, which is described in the paper. This tool was designed to provide teachers with a broad variety of cognitive and socio-cognitive functions of hypervideo for learning, so that we could address the second and most important goal, which is to build a framework for the functional integration of hypervideo in education. To this extent, we considered the connection between teaching and learning. More specifically, we set out to construct a basis for capturing the various teaching– learning scenarios in which hypervideo might play a functional role. In this endeavor, we adopted a design-based approach, as we aimed to develop a framework that would be meaningful for teachers and students alike, particularly with respect to the complexity they face on a daily basis. This design-based approach is mirrored in the article structure too, that alternates concrete examples or cases and more general theoretical perspectives that mutually inform each other.

Hypervideo and interactivity Hypervideo (HV) can be defined as a combination of digital video and hypertext, which draws largely upon audiovisual media as central parts of their structure. They consist of interconnected video scenes containing ‘dynamic’ hyperlinks that are available during the course of the video scenes and that refer to further information elements (such as texts, photos and graphics) (Zahn, Barquero, & Schwan, 2004, p. 276).

Although a few authors distinguish between the two terms from a technical point of view (e.g. Meixner, Matusik, Grill, & Kosch, 2014), hypervideo is often referred to as “interactive video” because of its unique affordances to involve learners and teachers in the exchange of information (see Sauli, Cattaneo, & van der Meij, 2017 for a discussion on the terminology). Therefore, in our discussion of HV, we will focus on the possibilities for interactivity. In our opinion, HV offers three distinct affordances for interactivity: control features, hyperlinks, and exchange options. This classification closely resembles that of Beauchamp and Kennewell (2008, 2010), who distinguish between the following forms of Information and Communication Technologies (ICT) usage: (a) a partner to interact with (i.e. control features); (b) a resource to interact about (i.e. hyperlinks); and (c) a medium to interact through (i.e. exchange options).

Control features Like regular video, most HV comes with a control feature in the form of either a slider or a classic toolbar that includes a play, pause, and rewind/forward button. The control feature enables users to interact with the HV in a way that best suits their capacities and needs as they process the basic instructional video material. For instance, one way in which the learner can benefit from control features is by moderating information intake. There are at least two factors that can make it hard for a learner to keep up with the ongoing stream of information in a video: complexity and transience. Complexity derives from scenes in which many things happen at once. Learners may be hard pressed to attend to all of the

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information presented (Renkl & Scheiter, 2015). Transience relates to the fact that videos present information in an ongoing stream. Learners may be obstructed in consolidating what has been understood because new information following in rapid succession (Höffler, Schmeck, & Opfermann, 2013). The presence of a toolbar offers learners an opportunity to deal with the risk of cognitive overload due to complexity and transience. With a toolbar, learners can pause a video when they need processing time and replay segments that are taxing. The functionality of the toolbar is nicely illustrated in Schwan and Riempp’s (2004) research, where participants received video instructions on how to tie a knot. Usage of the toolbar was found to co-vary with task complexity. Learners more often used the toolbar for pausing and replaying the video with more difficult knots. HV can also offer advanced navigational support and supply the learner with flexible ways to navigate within video. For instance, HTIMEL (HTML with Time Extensions; see Chambel, Zahn, & Finke, 2006) allows the user to better understand the video structure, which is made explicit through indexes synchronized with the video, like a table of contents (Figure 1, left) or an image map giving a visual summary of the video (Figure 1, right). The user can take advantage of any of the two indexes to navigate through different segments of the video. Similarly, HVet (Hipervideo Veterinario; see Tiellet, Pereira, Reategui, Lima, & Chambel, 2010) provides a table of content available both as an image index – where each labeled thumbnail corresponds to the beginning of a specific segment in the video – and as a structured text surgical index, which is also temporally linked to the video. The SIVA player (Meixner, John, & Handschigl, 2016) also provides selection panels for follow-up scenes, a drop-down table of contents at the top left corner of the video, and buttons to directly jump to the previous or following scene of the video. On the contrary, the Hyper-Hitchcock player (Shipman, Girgensohn, & Wilcox, 2008) shows both the link destinations and the jump-off points of followed links with keyframes appearing directly below the main video timeline. It is not by chance that the authors prefer in this case to speak about “detail-on-demand videos”. In this direction, HyperMeeting (Girgensohn, Marlow, Shipman, & Wilcox, 2015) represents a step further, constituting a “meeting chain”, i.e. a chain of video-recorded meetings forming a HV that links together segments of videos treating the same topic. The timeline of the currently displayed video shows both the labels about the topics treated in the corresponding sequences, and numbered circles indicating the linked videos. An important function of this navigational support in HV is that it facilitates the learner in selecting a non-linear trajectory through the video material. With a clickable index, table of contents, or graphlike representation (as in a concept map), learners can more easily navigate to pertinent video segments and profit from a structural overview of the domain.

Hyperlinks One of the first examples of exploiting the use of hyperlinks within a video is surely HyperCafe (Sawhney, Balcom, & Smith, 1996). From then on, apart from other well-known marketing-oriented

Figure 1. The HTIMEL interface and its table of content, both in the textual (left) and iconic (right) variants. From: (Chambel et al., 2006, p. 37).

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Figure 2. The HVet (Hipervídeo Veterinário) interface and its multilink feature, which enables the user to have links (1) that connect the video to further information (2). |From: (Tiellet et al., 2010, p. 6).

software like HyperSoap (Bove, Dakss, Chalom, & Agamanolis, 2000), HV interfaces often include hyperlinks that connect the video to existing, supplementary instructional materials. Such hyperlinks are signaled by hotspots or markers (Stahl, Finke, & Zahn, 2006). The links lead the learner to additional information in different formats (e.g. text documents, audio files, and images links). Supplementary materials can provide the learner with supportive arguments, contextualize the subject matter, and deepen or broaden the information about the topic. Figure 2 gives an example of how such a hyperlink feature is exploited by HVet (Tiellet et al., 2010). Sadallah, Aubert, and Prié (2014), further distinguish between hotspots, textual overlays and graphical overlays to introduce WebCHM, the evolution of Advene (Aubert & Prié, 2005), which the authors refer to as “active reading” systems. The hyperlink feature supports in helping the learner to connect different sources of information. Several studies have shown the benefit of using multiple representations to facilitate learning. van der Meij and de Jong (2006), for example, showed how a learning environment with integrated, dynamically linked representations led to better learning results than a learning environment with separate, non-linked representations or separate, dynamically linked representations. Because the hotspots are often spatially determined in hypervideo, they also serve an attentiondirecting role. In a study on the use of cinematic techniques in propaganda, Merkt and Sochatzy (2015) showed how the use of specific manifestation cues led viewers to deeper analyses and interpretation of video clips, thus confirming the positive effects of signaling also reported by Ozcelik, Arslan-Ari, and Cagiltay (2010).

Exchange options HV includes exchange options for teachers and learners to post comments or communicate with others. These options in HV tend to be rather varied. Although the term “annotation” is sometimes used in a wider sense (e.g. in Sadallah et al., 2014) to also include what we referred to within the category “hyperlinks”, here we use it more restrictively to indicate textual information inserted by the final user in the HV player interface – sometimes in fact such a function is limited to the editor, like in MOVieGoer (Zahn et al., 2004). Video annotation is a commonly used HV option for enhancing reflection, which has a strong tradition particularly for teacher education and professional

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competence development (please refer to Rich and Hannafin (2009) and Rich and Trip (2011) for a useful comparison of available video annotation tools in this domain). For example, Colasante (2011) showed how the use of a media annotation tool called MAT (Media Annotation Tool) within pre-service teacher training resulted in benefits for critical reflection on and evaluation of teaching practice. MAT enables learner to select areas of video and mark each of them with a “marker”. The marker is colored according to different analysis categories (e.g. “Notes”, “Teacher Feedback”, “Final Reflections”) and linked to an annotation area where the user can type and share text entries. Similar features are available in MediaNotes, which further provides advanced tagging and search capabilities (but actually the software is not developed any more). Tripp and Rich (2012) used MediaNotes to foster peer feedback among teachers. They concluded that the tool helped raise teachers’ awareness of practical details that had previously gone unnoticed, thereby increasing the teachers’ professionalism. Similar effects of the annotation tool have been reported in the medical domain (e.g. Hulsman & van der Vloodt, 2015), where the tool Video Fragment Rating has been used to provide feedback and contribute to ongoing professional development. HV occasionally includes a tool such as a weblog, which learners can use to exchange information collaboratively among each other and with the teacher(s). This was for example the use made of VideoANT (Hosack, 2010) by Ellis, McFadden, Anwar, and Roehrig (2015), or of WebDIVER (Zahn, Pea, Hesse, & Rosen, 2010). A variant that is quickly becoming more popular is the quiz feature, where the exchange option takes the form of feedback provided automatically by the system. Figure 3 presents an example of a HV with an embedded quiz feature: Zaption (see Stigler, Geller, & Givvin, 2015) is a platform that allows you to insert open response questions, multiple choice questions, and check box questions at any point in the video. It can also be used to show the learners the results based on their answers. In his study on the use of question-embedded interactive video environments, Vural (2013) showed that such technology allows students to enhance their achievement and improve learning effectiveness with respect to their peers using a simple interactive video. In addition to promoting learning, question-embedded video also improves the amount of time students spend interacting with the learning materials. Although it goes beyond the aims of the present paper, it can be however worthy to notice that the same interactivity features actually characterize also MOOCs and are proved to be discriminant as for their effectiveness for learning. For example, after analyzing MOOC video interaction patterns, Li, Kidzinski, Jermann, and Dillenbourg (2015) provide three design insights to improve MOOC effectiveness for learning; apart the first, dedicated to the improvement of the analytics algorithm, the other two are related to giving the users the possibility to quickly access the different portions of the videos (corresponding to the control features in hypervideos) and to provide them additional information when pausing the video in correspondence of particular video frames (corresponding to the

Figure 3. The Zaption interface and its quiz feature in the Tour Viewer. From: (Stigler et al., 2015, p. 16).

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linking function in hypervideos). Similarly, Hew (2016) investigated what are the key factors that could influence student engagements in MOOCs; out of the five factors identified, three are related respectively to having a variety of helpful course resources (corresponding again to the linking function), to supporting peer interaction and to allowing active learning, particularly through quizzes (both corresponding to the exchange options). Other studies show that the level of interaction with either the resources in the course or the people (instructor or peers) are strongly correlated with retention (Hone & El Said, 2016), completion (Pursel, Zhang, Jablokow, Choi, & Velegol, 2016; Swinnerton, Hotchkiss, & Morris, 2017) and grades (Tseng, Tsao, Yu, Chan, & Lai, 2016). To sum up, the versatility of hypervideo allows it to serve various instructional functions that can make video an effective instructional medium for learning. As shown by Chambel et al. (2006), if a hypervideo interface is carefully designed – to this extent the authors identify design guidelines to provide the user with control, consistency, context, familiarity and continuity – the hypervideo itself becomes a wonderful learning tool, able to support diverse learning styles and interaction among learners. Additionally “by allowing the viewer to watch video in her natural experiential mode, and by inducing and supporting more active and reflective attitudes, through control, comparison, and annotations, hypervideo can support both cognitive modes suggested by Norman (1993)” (p. 34). To make these potentials unfold in school-based education, thorough designs of hypervideo as learning environments and instructional settings are crucial. In the next section we will therefore extend our analyses of tool functions by adding a more general theoretical perspective that can inform targeted approaches in using hypervideo as an instructional medium for learning.

Hypervideo-supported learning and teaching Two complementary theoretical approaches can be used to inform designers about conditions and effective instructional uses of hypervideo: (1) the cognitive approach with its focus on information processing, and (2) the socio-cultural approach which highlights social interaction and context. For each approach, we will describe the main learning processes as well as its implications for design.

Hypervideo as a cognitive tool Cognitive viewpoints consider hypervideo a cognitive tool that can serve two important functions (Zahn, 2003): (1) Facilitating information processing by multiple knowledge representations (see | Clark & Paivio, 1991; Mayer, 2001, 2005; Wetzel, Radtke, & Stern, 1994), and (2) supporting cognitive flexibility by enabling non-linear information structuring and reflection (Chambel et al., 2006; Guimarães, Chambel, & Bidarra, 2000; Spiro & Jehng, 1990; Stahl et al., 2006). Multiple knowledge representation is an important issue in Mayer’s (2001, 2005) cognitive theory of multimedia learning (CTML), which is a dominant theoretical framework that explains how hypervideo can support learning. According to CTML, learning is an active process of selecting, organizing, and integrating information. This process happens within the human cognitive architecture which is characterized by limited capacity. Multimedia must therefore be designed in ways that do not overwhelm learners with too much information to process (see cognitive load theory, e.g. Sweller, 1988, 2011). In addition, there are two separate channels – the verbal and the visual channel – available for information processing. These channels act independently and can be used for parallel information processing and cognitive integration (in line with dual coding theory, e.g. Paivio, 1986). Such parallel processing can be exploited to overcome capacity limitations through proper design choices. Several principles for the effective design of multimedia for learning have been developed within CTML . For example, the signaling principle (i.e. people learn better when the organization of a lesson is highlighted) is used to reduce extraneous processing; the modality principle (i.e. people learn better from a multimedia presentation when words are spoken rather than printed) is used to manage essential processing; and the multimedia principle (i.e. people learn better from words and pictures than from words alone) is used to foster generative processing (Mayer, 2011). Applied to video this

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means, for example, that using visual cues to focus the learner’s attention on some details of the video is effective for fostering learning. There is considerable supporting empirical evidence for each design principle, and there are informed debates regarding their use in practice (e.g. Koumi, 2013). Spiro and Jehng’s (1990) Cognitive Flexibility Theory (CFT) is a complementary theoretical framework that specifically addresses non-linear structuring and reflection. CFT posits that in complex and ill-structured domains, learning should occur as a form of “crisscrossing landscapes” – a metaphor for accessing knowledge representations in non-linear and multi-thematic ways. In principle, this is equivalent to the hyper-structure idea. For instructional design applied to video, this means that video scenes should not only run as a linear sequence of segments, but should be controllable for learners and accessible from different pathways representing multiple content perspectives (e.g. by hyperlink access). Design suggestions serving these aims include providing video control functions (e.g. stop, rewind, fast forward) so that learners can control the information flow and take time for reflection. A further set of design principles relates to the pathways representing multiple thematic perspectives. Hypervideo can optimally serve both purposes. Important design principles would include first identifying relevant content perspectives, and then creating pathways for representing these perspectives. In hypervideo, this can be achieved by constructing “menus” with different content areas and “markers” for accessing information from different viewpoints. When the learners are creating a hypervideo, tools should enable them to create their own perspectives and selections from video clips and to move from these selections to other collections of video clips. In addition, there should be annotation and tags features for creating paths and comments on video segments (similar to Goldman & Dong’s suggestions, 2009).

Hypervideo as a socio-cognitive tool Socio-cognitive perspectives view hypervideo as a tool for enculturation and collaboration (Zahn et al., 2010; Zahn, Krauskopf, Hesse, & Pea, 2012). Hypervideo should give people the opportunity to engage in the discourse, practice, and thinking of a community (see Lave & Wenger, 1991; Wenger, 1998). Such participation can lead to distributed and shared knowledge, as seen in knowledge-building communities (Scardamalia & Bereiter, 2006). Learning is considered a situated (Brown, Collins, & Duguid, 1989) cultural phenomenon that occurs outside and inside schools, at work, and in all kinds of informal settings. Anchored Instruction is an important theoretical framework for the socio-cognitive perspective (Cognition and Technology Group at Vanderbilt, 1990, 1992, 1993). According to this view, learning of abstract knowledge is facilitated when people can anchor such information with concrete situations or cases. Anchors (problem contexts) are better given in an audiovisual than a textual format because the former “allow students to develop pattern recognition skills” and allows for “a more veridical representation of events than text” (Cognition and Technology Group at Vanderbilt, 1990, p. 3). A multimedia presentation, such as video, can present information in a dynamic, visual, and spatial form, which enables students to more easily construct rich mental models of the problem state. Design principles that fit this view indicate that instructional materials should introduce and illustrate authentic real-world problem(s) vividly, and provide students with additional resources that enable them to connect information elements to the problem representation (e.g. integrating textual information in a video via a marker). With respect to the contribution of hypervideo for collaboration, the Computer-Supported Collaborative Learning (CSCL) approach has advanced important insights on how to stimulate (peer) interaction and achieve cognitive elaboration. Peers can provide information, help, and explanations to their fellow students. Additionally, peer interactions can stimulate further learning mechanisms such as joint meaning making, cognitive conflicts and the subsequent search for additional

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information (Piaget, 1985), conceptual convergence in collaborative problem solving (e.g. Roschelle, 1992), and observational learning (e.g. Bandura, 1986). Design suggestions for collaborative hypervideo should include the possibility of collaborative interaction through an interface that affords shared annotations. In addition, focused discussions will require discussion areas to allow for elaborate discussion threads that may result in dynamic information spaces for learning (Zahn et al., 2010).

The iVideo.education hypervideo interface The extensive analysis of existing HV software in the section above evidenced that most of the existing platforms to date can be ascribed to one of the theoretical frameworks proposed in the previous section. However, with regard to the interactivity features we highlighted, existing hypervideo tools were not found yet that provide the user with all three features at the same time (see Table 1). This prompted us to design the iVideo.education (formerly, iVideo.education) platform, a HV program that includes affordances of user control, hyperlinks, and exchange options in a single interface. User control is facilitated by the following: . .

a regular toolbar (see #1 in Figure 4) that allows the user to play/pause/stop and rewind/forward the video, to adjust the volume, and to set the width of the screen; a segmentation in chapters (see #2 in Figure 4): the user can directly jump to a video segment by clicking on a chapter from an expandable menu. In the expanded view, the menu shows the active points in each chapter (see below). Hyperlinking is facilitated by the following:

.

Markers or active points (see #3 in Figure 4) that consist of blinking, clickable hotspots that appear for a defined period of time on the video screen and that give access to supplementary resources of different types and formats (e.g. texts, pictures, documents, audio, and links). You can also

Table 1. Synopsis of the main interactivity features of existing hypervideo tools, compared to the iVideo.education tool.

Toolbar

Table of content / Index

Hyperlinked materials

Annotation

Quiz

Software

Reference Paper

HTIMEL

Chambel et al. (2006) Tiellet et al. (2010) Meixner et al. (2016) Shipman et al. (2008) Girgensohn et al. (2015) Sadallah et al. (2014) Colasante (2011)

X

X

X

X

X X

X X

X X

X

X

(X)

X

X

X

X

X

X

X

X

(X)

X

Tripp and Rich (2012) Hulsman and van der Vloodt (2015) Hosack (2010) Zahn et al. (2010) Stigler et al. (2015)

X

(X)

X

HVet SIVA Player Hyper Hitchcock Hyper Meeting Web CHM Media Annotation Tool (MAT) Media Notes Video Fragment Rating VideoANT DIVER/WebDIVER Zaption iVideo.education

Individual

X X X X

(X)

X

X

X

X

X

X

Multiple

Comment

X

X

X

X

X

X X

X

X X

X

X

X

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Figure 4. The iVideo.education interface and features (1 = Toolbar; 2 = Chapter segmentation; 3 = Markers; 4 = Quiz; 5 = Instructional information).

access the hotspots directly in chapter menus. These hotspots can be named for easier navigation. The hotspots in a video can be made compulsory; in this case the video stops automatically when an active point appears on the screen. The iVideo.education HV displays three marker types that each has its own distinct function. A red circle is used for directing the learner’s attention to a detail of the video. A blue triangle refers the viewer to a video segment. A green square refers viewers to a task that needs to be performed. Exchange options are facilitated by the following: .

.

Individual video annotation (see the left-hand side of Figure 5) is enabled with a “Notes” tab that allows the individual user to make posts and notes on a notepad with basic editing features. Posts and notes can be saved in PDF format, along with the annotated frame. Collaborative video annotation (blog-like; see the right-hand side of Figure 5) is enabled with a “Comment” tab. It has the same storage capacity as the individual tool, only in this case

Figure 5. iVideo.education’s individual (left) and collaborative (right) video annotation feature.

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different users can contribute. For instance, the saved PDF file can include a lengthy conversation between different persons. The quiz (see #4 in Figure 4) is a marker represented by a question mark. In a quiz, it is possible to present a multiple choice question with up to five true or false answers. Feedback to the answers is given in the form of right/wrong icons.

The player interface (the player) is the end result of a series of design actions that transform a raw video into a hypervideo. iVideo.education also includes an authoring tool (the editor) in the form of a graphical user interface with which designers can create the three interactive features of the HV. In addition, the editor allows (a) the insertion of labels (subtitles) to name and draw attention to a screen element, and (b) the insertion of information from the opening screen of a video so that the user is informed of the main instructional objectives of the video at all times (see Hobbs, 2006).

Integrating theoretical perspectives and practical experiences into a design model Dimensions of a design model for hypervideo-based learning scenarios In addition to concrete HV tools and general learning theories underlying their design concepts, one also has to consider the process of designing scenarios when planning to use HV in classrooms. This process is a complex teacher-centered design task and respectiveguidelines are usually provided by instructional design models. Combining the above-mentioned theory-based principles with our own experiences from the use of the iVideo.education software tools, we derived the following model for designing hypervideo-based teaching and learning scenarios (see Figure 6). A preliminary, raw version of the model was described in Cattaneo, Nguyen, and Aprea (2016a), here we further elaborate both on its theoretical foundations and the assumed dimensions in order to better ground, define and structure it. The model includes two intertwined dimensions that the teacher must consider: the (hyper)videorelated design phase and processes and the involvement of the different actor(s) therein. The first dimension deals with the phases and tasks involved in the design of hypervideo-based learning scenarios. More specifically, this dimension includes the following: 1) A preparation phase, comprising both the identification of the reference raw video and its editing; 2) a production phase, devoted to making the video interactive, thus producing a hypervideo; and 3) a use phase, in which the hypervideo is employed as learning material. The whole process and its sub-steps are summarized in Figure 7. The second dimension refers to the instructional strategies that a teacher may want to employ. Smith and Ragan (1999) characterize these strategies according to their locus of control. That is, the authors distinguish the contrasting generative and supplantive strategies. In generative strategies, “learners generate the preponderance of information processing during learning by providing

Figure 6. A matrix visualization of our design model.

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much of the events of instruction themselves. Such instruction has low levels of scaffolding (instructional facilitation)” (p. 124). In other words, in generative strategies, most of the responsibility for making the decisions in preparing, producing, and using a hypervideo-based learning scenario primarily rests with the student. In contrast, “supplantive strategies explicitly and overtly provide much of the events of instruction, actively gaining learners’ attention, informing learners of the objective, explicitly providing a preview of the lesson, and so on” (p. 124). In short, the teacher is mainly in control with these strategies.

Figure 7. The process of designing a hypervideo-based instructional scenario.

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The authors point out that both strategies have their specific pros and cons. For example, whereas generative strategies are expected to be superior with regard to deep-level learning, they may be time-consuming and can overtax students at the start of a learning path. In contrast, supplantive strategies can help learners concentrate on the relevant aspects of instruction and yield learning outcomes more efficiently. However, students might experience these as boring and demotivating and feel that, in the long run, they undermine their autonomy and self-reliance, creating “learned helplessness” (Seligman, 1975). Smith and Ragan (1999) therefore conclude that the two strategies are not a question of either/or; rather, they demark the poles of a continuum in which the instructional designer/teacher has to make a decision on the optimal degree of instructional facilitation. This decision particularly depends on the following: (a) the specific prerequisites of the learners (cognitive, motivational, attitudinal); (b) the type of task; and (c) the context (e.g. goal priorities and available resources). Depending on the design choices and on their combination, then, different paths of integrating hypervideos in learning activities are possible, based first on the identification and editing of a raw video, which can be an issue for the teacher (box A in Figure 6) or for the students, alone (B) or as a group activity (C); then on the hypervideo production, which can be done again by the teacher (D), or proposed to students as an individual (E) or collective (F) learning by design activity; and finally, the hypervideo can be used directly controlled by the teachers as a support for their lessons (G), or manipulated by students, who can interact with it individually (H) or in groups (I). Appendix 1 describes the building blocks that the teacher or designer must consider when creating hypervideo-based instructional scenarios. These blocks are grounded in both the theoretical frameworks and the design principles presented above. In the following section, different exemplary cases of hypervideo-based instructional scenarios are presented.

Hypervideo-supported teaching: illustrating some instructional cases Now that we have introduced in more detail the components of the different layers of design choices that an educator has to pass through when integrating a hypervideo in an instructional scenario, we can illustrate how such scenarios can take form in an ecological setting. We worked with teachers from the vocational education and training (VET) sector who volunteered to use the hypervideo in their teaching practice. They completed a training course to learn how to use our authoring tool, which was then placed at their disposal. They also received brief general instructions on the main principles of multimedia learning (|Mayer, 2001, 2005). They were then asked to design, create, and test at least one hypervideo-based scenario for use in their classes. Some of them created more than one, in this case profiting from the first experience to design a different scenario. The involved professions covered the whole spectrum of VET/PET, as classified by Lucas, Spencer, and Claxton (2012). As a consequence, the content also differed, ranging from procedural knowledge related to the specific profession (e.g. how to thread a needle with clothing designers, how to conduct a consultancy with office clerks, how to manage composite materials molds with auto body repairmen) to declarative or conceptual knowledge (e.g. cloud computing with IT technicians, ethics with health-care operators, second language learning with several curricula). More details regarding several of these case studies are available in Cattaneo et al. (2016a). For the sake of our contribution here, let us add that the selection of exemplary cases we present below is mainly driven by the intersection of the two major components introduced so far: On the one hand, the exploitation of the different kinds of interactivity the hypervideo allows for (and related features in the player), and on the other hand, the variations on the continuum between supplantive and generative strategies. In so doing, we could identify five main scenarios. In presenting each of them, within the title we make reference to the letters of Figure 6. to identify the scenario path. Besides, we mainly refer to and describe one single case, making reference to other cases in the same category when needed.

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Scenario 1. Everything in the teacher’s hands (A-D-G path) Fred is a mechatronic teacher with some years of experience. He is teaching part-time, as he also kept his job in a garage. For the preparation phase, he is reminded of a situation he experienced as a mechanic in the past, which could be useful to address several competences of the profile, both on the professional side (electrotechnics) and on the methodological and personal side (e.g. how to treat a customer). He then writes a storyboard of the situation, and with the help of our multimedia laboratory, he simulates the situation and records a video clip in a real garage (duration: 7′ 12′′ ). For the production phase, he works on the video to integrate additional materials in the form of pictures, schemes, and documents. This makes it possible to link the content in the video with the underlying theory, thus exploiting the hyperlink function. The resulting hypervideo is used in a second-year class (N = 20; Mage=18.90; SDage=3.38) to manage a lesson: the video is shown on a big screen, directly controlled by the teacher, and the interactive points are used to emphasize critical information, involving the learners in the discussion (Figure 8). This first scenario is located on the supplantive side of the continuum, especially exploiting the hyperlink feature of HV, used as a teaching material to support the teacher’s lecture. In our experience, the very first use of a hypervideo by teachers overlaps with this scenario. One of the possible variations is that the raw video can often easily be produced by the teachers themselves with an amateur camera.

Scenario 2. Allow the learners to determine the pace (A-D-H path) George is an information technology teacher with a few years of experience. He is also a software developer and owns a small company. He wants to use the hypervideo tool in one of his first-year classes (N = 12, Mage=16.42, SDage=1.38) to introduce the topic of computer security. In the preparation phase he chooses to look for an existing video, which he finds on the Internet. The video (10′ 46′′ ), taken from a conference, illustrates a practical case. The teacher decides to take care of the production, making the video interactive and adding follow-up materials (most of which contain definitions of the technical terms mentioned in the audio along with deepening links) and quizzes. The learning activity takes place in the computer lab, with learners working independently, each with their own computer (Figure 9). At their own pace, the learners explore the hypervideo, accessing the active points and answering the quizzes. The teacher is at their disposal for any questions. After the personal viewing, the learners work on a task asking them to make connections between the video and their daily experience and to provide arguments for their answer.

Figure 8. A lot of hyperlinks are inserted in the hypervideo, managed by the teacher in class.

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Figure 9. Students work individually at their own pace in the computer lab.

With respect to the interactivity, the distinctive feature of this scenario is that the viewing control is given to the learners, who can access the information they want in the order and pace they want; additionally, the quiz function allows for some exchange options. This moves the scenario a bit toward a more generative strategy with respect to the first scenario, even if the preparation and production phases are still completely the teacher’s responsibility.

Scenario 3. Let us work on learners’ experiences, with the teacher’s expertise (B-D-G path) Mike teaches chef apprentices and is himself a former chef. He is used to introducing professional videos in his lessons, but he complains that the situations shown in such videos are too far from apprentices’ reality (such videos usually show a famous chef in a white, aseptic kitchen) and that the link between what is shown in practice and the underlying technical principles is not easy to show. For this reason, he asks some apprentices to volunteer and use a head-mounted action camera in their workplaces to provide some authentic videos on specific cooking methods (e.g. how to glaze vegetables). Then, he edits some pieces of footage to be included in one hypervideo to show, for example, how the same cooking method has different effects, depending on the product (carrots vs. shallots) or the workplace context (glazing in a high-ranked restaurant vs. glazing in a company canteen), as tools, labor divisions, and norms can vary enormously. He also personally introduces some active points on frames that are particularly relevant for the procedure. He especially exploits the possibility to focus the attention on specific details and to insert short reflective questions as a text. The resulting hypervideo (7′ 55′′ ) is then used in a first-year class (N = 26; Mage=16.8; SDage=1.32) as a support for guided interaction: the teacher profits from the fact that the video footage has been provided by some apprentices, as he can begin by asking them to comment on what they were doing (Figure 10). The active points function as an aid to enlarge the discussion with the other members of the class and for the teacher to eventually provide additional information rooted in his expertise. With respect to the interactivity features, this scenario is similar to the first one, as it mainly exploits hyperlinking. The teacher is also responsible for controlling the viewing itself. However, this scenario places closer to generative strategies, as most of the preparation phase is given to the learners and they also have a central role in the use phase.

Scenario 4. Role-playing and video analysis of professional practice (B-(D)-H path) Robert is a consultant in the commercial field. He has also worked as an instructor for a corporate association for many years. He has to address the following topic: “How to manage customers’ consulting”.

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Figure 10. Student-generated clips commented on during the class directly by the authors.

In the preparation phase, Robert provides the students (in groups) with some materials for preparing the consultancy. Then each group selects one person to perform a role-play, with a fake customer following a script. The simulation is video-recorded. In the production phase, two clips from two groups are put together and inserted in the hypervideo interface. No additional information is integrated. In the use phase, each student uses the video annotation tool to analyze the video (Figure 11), after listening to a lecture accompanied by a demonstration video. The notes are then used in class (all the details are discussed in Cattaneo & Boldrini, 2016b). The whole scenario relies on the video annotation feature to support individual analysis. Additionally, the learners are responsible for providing the raw video. The teacher orchestrates the lesson and provides the modeling clip, but does not intervene in the hypervideo design itself.

Scenario 5. The learners always on the stage (C-F-(H) path) Jack teaches surgery room technicians. He addresses certain procedures in the domain of adenotonsillectomy with his first-year class (N = 16, Mage=25.29, SDage=6.03). As a first step, he holds a lecture about the procedure, focused on the technical vocabulary. Learners are also given a document containing guidelines for performing the procedure. Starting from their own prior knowledge and personal interests, four groups, each comprised of four people, are established. Each group is assigned a specific part of the whole procedure. The teacher asks the students to identify possible questions concerning their assigned topic and to find the answers both autonomously (e.g. through texts made available by the teacher or by using the Internet) and through discussion. He addresses the unsolved questions in an intermediate plenary briefing. Afterwards, the students begin to develop a storyboard to illustrate the different steps of the procedure by means of a video (with themselves as actors). A week later, the simulation phase commences in the surgical room they use for training. The procedure is recorded (Figure 12). Those students who are not directly involved in the simulation observe carefully and take notes.

Figure 11. Students’ video analysis using the annotation tool.

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Figure 12. Students’ role-playing and following a discussion on what to insert as hyperlinks.

Such notes provide a useful starting point for deciding what additional information to insert in the hypervideo, which happened some days later, with the whole class. The teacher shows the videos and the students comment on all of them, identifying errors and focusing on the most important content. All the students contribute actively, sharing observations and questions from their lived experience or the notes. This discussion occurs virtually at a distance as well, as the teacher uploads the raw videos to the web portal and launches the collaborative annotation feature. The completion of the production phase takes place a week later in the classroom. Step by step, on the basis of their indications, the teacher builds four hypervideos, completing the information as he thinks necessary. The final products are then available to the apprentices as learning material. No use of the resulting HVs is done in class. This fifth scenario exploits all four levels of interactivity, including collaborative annotation, and explicitly moves toward a completely generative instructional strategy, where learners design the raw video and the hypervideo.

Conclusion The present contribution aimed at elaborating on a model for supporting design decisions about effectively using hypervideo in instruction. The inquiry grounds its theoretical roots in (socio)cognitive science and instructional design, and profited from a design-based research approach to investigate the possibilities to integrate hypervideo in ecologically valid design experiments conducted in vocational education. This led us to the following three main results: First, an easy-to-use (Cattaneo, Nguyen, Sauli, & Aprea, 2015), theory-coherent software tool to create hypervideo, available for both teachers and students. Although we have shown its uniqueness in the landscape of hypervideo software solutions, with its capability to cover all the three main affordances related to interactivity in the same interface, we do not pretend it to be free from possible improvements and further development. For example, compared to some of the alternatives presented, our solution mainly exploits the characteristics of a heterogeneous hypervideos, missing the ones coming from homogeneous hypervideos (Chambel et al., 2006): To foresee the possibility to create video-to-video paths (as in Hyper-Hitchcock or in HyperMeeting) and the possibility to have visual indexes (as in HVet, HTIMEL, or WebCHM) could be considered worthy to further increase the control features. Similarly, to integrate the possibility to add – and search through – keywords, tags, or codes (as in the SIVA player, MediaNotes, and MAT), and the possibility to have a wider interaction with both teachers and peers (as in most of the MOOC platforms, like Coursera or Kahn Academy) would improve the exchange options features. Second, a set of authentic cases that can inspire educators about possible instructional uses of such a tool (see also Cattaneo, Nguyen, & Aprea, 2016a). Although the five scenarios already constitute a good variety, many other combinations are still possible and deserving further investigations. Third, and most important,the wished-for design model, organized around three main design

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phases and supplied with a detailed workflow of all the intermediate design steps (see Figure 7 and Appendix 1). This last result constitutes a valuable resource for teachers and trainers to reflect on and design interventions using hypervideo. Independently from its origins within vocational education, it can be easily transferred and applied to other educational or instructional contexts. The model and its building process can also be helpful for researchers in order to identify recommendations for further investigations on the topic that could not be covered in this paper, in terms of both the design and instructional layers. In the former case, possible topics of investigation are connected to the cognitive and socio-cognitive implications of the use of single or multiple levels of interactivity. In the latter case, the conditions for the real effectiveness for learning of the possible scenarios, controlling for the different contexts, learners’ characteristics, and learning tasks remain a significant and open question.

Disclosure statement No potential conflict of interest was reported by the authors.

Funding This work was supported by Swiss State Secretariat for Education, Research and Innovation (SERI) [grant number 131536].

Notes on contributors Alberto Cattaneo is Head of the Research Field “Innovation in VET” at the Swiss Federal Institute for Vocational Education and Training (SFIVET). He got his PhD in Social, Developmental and Organizational Psychology, discussing a thesis on Blended Learning and Virtual Learning Environments. His actual main research fields concern the integration of ICT – and especially video-based technology – in teaching and learning, reflective learning in VET, instructional design, multimedia learning, teachers’ training. Hans van der Meij is Senior Researcher and Lecturer in Instructional Technology at the University of Twente in the Netherlands. His research interests are: questioning, technical documentation (e.g. instructional design, minimalism, the development of self-study materials), and the functional integration of ICT in education. He has received several awards for his articles, including a “Landmark Paper” award from IEEE for a publication on minimalism (with John Carroll). Carmela Aprea is Full Professor of Business and Economics Education at the Friedrich Schiller University Jena (Germany). She holds a Diploma Degree in Business and Economics Education from the Goethe University Frankfurt (Germany) and a PhD in the same field from the University of Mannheim (Germany). Florinda Sauli is scientific collaborator at the Swiss Federal Institute for Vocational Education and Training (SFIVET). She holds a Master in Social Policies and Development. She currently works on the Interactive Videos for Vocational Education and Training (IV4VET) project, which investigates how to integrate hypervideos in instructional scenarios. Carmen Zahn works as a full professor at the School of Applied Psychology (APS) - University of Applied Sciences and Arts in Northwestern Switzerland. Her current research projects focus on video-based knowledge processes in learning and teaching. Carmen Zahn received her doctoral degree at the Faculty of the Cognitive Sciences at the University of Tübingen in 2004, where she also completed her habilitation in 2010.

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Appendix 1. Building blocks of a design model for hypervideo-based learning scenarios Preparation phase: identify and edit the reference raw video. a. Identify the reference raw video. For this very first decision, you can either create a video from scratch or start from an already existing video. In the former case, you have the following two possibilities: 1. Define a script or a storyboard to reproduce specific situations on the basis of a plot outline. In this case, what you will fix in the video is predetermined and simply reconstructed and simulated on the basis of a work plan. The design of the storyboard is extremely important in this case (see Schwartz & Hartman, 2007 for a framework applicable to this kind of video design). 2. Start from the assumption that video-recordings of “natural”, authentic situations are potentially rich with elements that are interesting for learning. As an intermediate possibility, predetermine the kind of situation you want to work on (e.g. by defining the procedure to be recorded a priori). In the latter case, while you do not need to design the raw video, you must devote an appropriate amount of time to searching and selecting the video. The use of search engines from radio and television archives and specialized websites could facilitate the task; however, the common websites based on videos – provided that the copyright law in force where the video will be used is respected – can offer a wide source of materials (see DeCesare, 2013 for further information on the topic). In both cases, you must define ad hoc criteria for the selection or the production and for the typology of contents to be addressed in the video. Depending on the instructional strategy you want to promote (and also considering the learners’ characteristics, the context characteristics, and the learning task), you can decide to personally choose an existing video, to produce it yourself, or to ask your students to provide you the video (either by looking for it or by producing it from scratch), individually or in a group. It is important to focus on scaffolding each of these possibilities with adequate guidelines. b. Edit the raw video. Edit the video. Now you need to prepare the video in order to transform it into a hypervideo. We are not referring here to the technical characteristics (format, quality, and encoding parameters) of the video, but rather to the specific relation of the audiovisual material with the addressed contents (see, for example, Andrist, Chepp, Dean, & Miller’s [2014] contribution concerning sociology). The length of the editing phase will vary depending on the learning objectives and on other requirements, going from a minimum intervention for cutting the appropriate video scene out, to more considerable changes for assembling several clips, to a veritable full editing. Be attentive to the length. The overall length of the video is very important. You must continue to consider the quantity of information included in any video (because of its intrinsic dynamic nature) and the fact that a hypervideo per se includes other additional information; on this basis, reduce the duration of the video as much as possible. If possible, do not exceed the length of six minutes (Guo, Kim, & Rubin, 2014) in order to avoid exceeding the learners’ available cognitive resources. Design the audio. Depending on the instructional strategy you selected for using the hypervideo, this step is either unnecessary or fundamental. For example, if you want to orally comment on the video in front of your classroom in a supplantive lecture, you can also profit from a mute video. On the contrary, if you want the learners to use it autonomously at a distance, given the importance of the complementary relation between the visual and the audio channels in fostering learning, the audio requires a cautious and attentive design. The relationship between the two elements has to be self-evident and synchronized. If you are designing a hypervideo to be reused in different scenarios, consider the most inclusive one so that the hypervideo can be adapted to all of the selected strategies. Production phase: make the video interactive Once you have prepared the reference video, you must take the following steps to make it interactive: (1) Segment the video in content units, introducing suitable labels to semantically characterize each segment or chapter; (2) Micro-design the hotspots, defining the following for each of them: a. Its function with respect to the content and ultimately to the learning objectives. b. The nature of the hotspot. In our software, for example, a hotspot can allow for an in-depth examination; it can be used to ask students to carry out analysis, reflection, and production tasks (with or without the annotation tool); or it can enable the students to self-evaluate their learning (e.g. through the quiz tool).

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c. The position in space and time. The position in space can be exploited to focus the learner’s attention on a detail of the frame, which is particularly relevant with respect to the addressed content; define such a position in a way that it does not impede the access to the information to be highlighted (e.g. awkwardly positioning the hotspot over the detail to be emphasized). Not all the hotspots require a spatial characterization: If the hotspot refers to a whole sequence of the video (e.g. privileging the audio content over the visual content), the spatial definition will not be required (which will, of course, have consequences for the choice of the hotspot; see previous point). The position in time (duration) requires one to define the starting point from which the hotspot will be visible and its duration (finishing point); in this case, you should also pay special attention to the relation between the content of the hotspot and the visualized frames in order to ensure that the hotspot does not refer to the wrong content in the video (and related audio). d. Additional materials. In order to avoid cognitive overload, carefully select the additional materials linked to each hotspot with respect to their offering alternative representation of the topic showed (e.g. a scheme or a technical sheet). Doing so will reinforce the link between theory and practice, show alternative fields of application (transfer), or simply provide a further layer of information for deepening the topic. Depending on the instructional strategy you are selecting, the design of the hypervideo can be handled by the teacher or assigned to the students. In this latter case, the students can work individually (e.g. when involved in a project work) or collaboratively in couples or in groups. Use phase: use the resulting hypervideo as instructional material This final step mainly concerns the instructional strategy the scenario is based on. If this strategy is rather supplantive, the teacher will use, for example, the hypervideo in front of the class as a teaching material. On the other hand, when selecting the most generative instructional strategies, you do not have to necessarily include this third step in the scenario, as it is resolved in the first two steps (you entrust the design to your learners as a route to learning). Accordingly, the level of interactivity can vary as well and can be assigned to the teacher or given to the learners.