Abstact 3

RESEARCH ARTICLE
Supporting motivation, task performance and retention
in video tutorials for software training
Hans van der Meij1 • Jan van der Meij2 • Tessa Voerman1 •
Evert Duipmans3
Published online: 19 December 2017
Ó The Author(s) 2017. This article is an open access publication
Abstract Video tutorials for software training are becoming more and more popular, but
their construction and effectiveness is understudied. This paper presents a theoretical
model that combines demonstration-based training (DBT) and multimedia learning theory
as a framework for design. The study investigated the effects of video tutorials on moti-
vation, task accomplishment and learning with special attention being paid to the role of
reviews. Three tutorials were compared: preview and demonstration (control condition),
preview and demonstration and review (review condition) and preview and demonstration
and 2nd demonstration (2-demo condition). Participants were 65 students from the upper
grades of elementary school. Participant logs revealed a significant decrease in coverage
for video types following the preview. All tutorials significantly raised self-efficacy and
procedural knowledge (i.e., task performances during training, immediate and delayed
post-test), but no effects of condition were found. The discussion addresses issues con-
cerning the design of the tutorials (overlap between video types) and usage conditions
(blocked video access during training tests) that may have negatively affected coverage
and the effectiveness of the reviews. A limitation of the study is that no process data were
& Hans van der Meij
h.vandermeij@utwente.nl
Jan van der Meij
j.vandermeij@utwente.nl
Tessa Voerman
tevoerman@gmail.com
Evert Duipmans
evert@duipmans.nl
1
Department of Instructional Technology, Faculty of Behavioural, Management and Social
Sciences, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands
2
Department of ELAN Teacher Development, Faculty of Behavioural, Management and Social
Sciences, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands
3
Saxion, Maarten Harpertsz, Tromplaan 28, 7513 AB Enschede, The Netherlands
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Education Tech Research Dev (2018) 66:597–614
https://doi.org/10.1007/s11423-017-9560-z

gathered that could shed light on the relationships between design features and observa-
tional learning processes.
Keywords Computer-mediated communication Á Elementary education Á Multimedia
systems
Introduction
The video tutorial is rapidly gaining ground as an instructional means for software training.
Companies such as Adobe, IBM, Microsoft, SAP and TechSmith are accommodating their
clients’ need for instructional support by developing a rapidly growing set of video tuto-
rials. For instance, TechSmith provides a wide range of video tutorials that help expand the
user’s skills in handling their programs. For their screen capture program SnagIt, the user
can find videos on how to accomplish basic tasks, including screen capturing, editing a
capture, and media sharing (TechSmith 2017, June 4). A further sign of the rising popu-
larity is the large repository of video tutorials for software training on the website
Lynda.com which recently was sold to LinkedIn in the amount of $1.5 billion (Kosoff
2017, May 2). Although video tutorials for software training may be increasingly popular,
it is unclear how well they work. There is no published information about the design
characteristics and effectiveness of the video tutorials produced by the aforementioned
companies.
Empirical studies that have compared video-based to paper-based tutorials for software
training have shown mixed results. While Mestre (2012) reported an advantage of paper-
based instructions, Alexander (2013) found no differences. Three other studies found the
video tutorial significantly more successful than the paper-based version (Lloyd and
Robertson 2012; van der Meij and van der Meij 2014, 2015). What this research suggests is
that effective videos should capitalize on the affordances of video while also attending to,
and possibly even incorporating key qualities of print.
van der Meij and van der Meij (2014, 2015) also reported the presence of a considerable
discrepancy between aided and unaided task performances for the video tutorial. Their
findings showed was that the demonstrations of task completion were sufficiently clear to
enable the users to perform the modeled tasks, but failed to achieve the same level of
success for learning. This result was seen as a signal that there was a need for additional
support for the user’s retention. A similar finding was obtained in another study by van der
Meij (2014) involving the same video tutorial.
The findings led to an elaboration of design guidelines and new empirical studies.
Specifically, a theoretical model was proposed consisting of a combination of demon-
stration-based training (DBT) (Grossman et al. 2013) and multimedia learning theory (e.g.,
Mayer 2014). Subsequently, a video tutorial for software training was designed in
accordance to the model and three experiments were conducted to test the effectiveness of
including complementary review videos (henceforth reviews) for enhancing learning (Brar
and van der Meij 2017; van der Meij and van der Meij 2016a, b). By and large, these
studies found positive effects of reviews.
The present study continues this line of research on reviews. First, the paper briefly
summarizes the theoretical model as a guide for constructing a video tutorial for software
training. Next, a discussion follows concerning the retention process and the benefits of
complementing demonstrations with reviews. The remainder of the paper discusses an
598 H. van der Meij et al.
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experiment on the added value of reviews for a video tutorial constructed using the
guidelines outlined by the theoretical model.
A theoretical model for software training
The video tutorial for software training that we designed consisted of a demonstration of
task performance that users could mimic and learn from, and that should also be of interest
to them. Figure 1 depicts the theoretical model that formed the basis for this construction
effort. At the heart of the model, there are the four fundamental processes involved in
(re)ProducƟon
User characterisƟcs
• Signaling (A1)
• Preview (A2)
• Pace (A3)
• User control (A4)
• PracƟce (P1)
• PracƟce Ɵming (P2)
• PracƟce ﬁles (P3)
• Anchoring in task domain (M1)
• ConversaƟonal style (M2)
• Music (M3)
• Length (M4)
ObservaƟonal learning
processes
AƩenƟon
RetenƟon
(OrganizaƟon &
IntegraƟon)
CogniƟve
Behavioral
InstrucƟonal features Outcomes
MoƟvaƟon AﬀecƟve
SituaƟonal variables
• SegmentaƟon (R1)
• Labels (R2)
• Simple-to-complex (R3)
• Pauses (R4)
• Review (R5)
Fig. 1 Theoretical model for video construction for software training. All features, except R2 and M3, were
incorporated in the design of the tutorial in this study
Supporting motivation, task performance and retention in… 599
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observational learning distinguished by Bandura (1986). Connected to these processes are
instructional features that, according to demonstration-based training (DBT), are necessary
to increase learning (Grossman et al. 2013; Rosen et al. 2010). The instructional features in
the model also connect to multimedia learning theory (see Mayer 2014) with its important
insights on (limitations of) cognitive processing and large set of empirically tested prin-
ciples for instructional design.
Under the umbrella term DBT, the model has recently been described in detail (Brar and
van der Meij 2017; van der Meij and van der Meij 2016a, b). The next section briefly
describes the retention process and summarizes the research on reviews. The subsection on
‘‘Instructional materials’’ in the ‘‘Method’’ details how specific instructional features from
the theoretical model found their way into the design of the video tutorial.
Notice that the theoretical model also takes into account user characteristics and situ-
ational variables. A user characteristic that should always be considered when seeking to
optimize learning is prior knowledge. Research on the expertise reversal principle has
shown that design features that are effective for novices or beginners may not be effective
or may even hinder learning for more knowledgeable people (Kalyuga 2007, 2014). Sit-
uational variables also constrain the design guidelines that can be applied. For software
training, the prototypical context is the individual user working alone at his or her com-
puter. Accordingly, the model does not mention various types of instructor-led support.
Complementing a demonstration with a review video
Retention involves the process of transforming incoming information into symbolic codes
that are stored in long-term memory (Bandura 1986). The user must extract the distinctive
features and structures from a task demonstration and code these into a succinct, proto-
typical representation. This information must be committed to memory to serve as a guide
for subsequent action. Retention, thus, subsumes the processes that Mayer (2008) refers to
as organization and integration. The end result should be a concept of task performance
that can serve as a guide and standard, enabling the user to organize, initiate, and monitor
future actions (Bandura 1986).
Figure 1 shows various design features that can support retention. The original video
tutorial used in van der Meij and van der Meij’s (2014, 2015) studies incorporated several
of these features in its design (i.e., segmentation, simple-to-complex sequencing, and
pauses). Still, additional support is needed to enhance user’s retention. Including a review
feature, which summarizes relevant information of a task performance, in a video tutorial
might strengthen the user’s retention, recall and task performance.
A literature search of empirical studies on how people summarize multimedia presen-
tations showed no hits. Thus, a literature search on text representation and recall has been
conducted. According to Meyer (1975, 1984), proficient readers adopt a structure-based
strategy to create a complete and coherent representation of an expository text. In such a
strategy, the reader identifies the overall top-level structure (e.g., sequence) of the
rhetorical relationships between the main ideas in a text. This structure is then used to
organize comprehension and recall. Readers who adopt a structure-based strategy have
better understanding and recall of the main topics of a text (Meyer and Poon 2001).
Moreover, they are in a better position to recall subordinate content as well (Meyer 1975).
Less proficient readers do not automatically use a structure-based strategy, but they benefit
from scaffolds that reveal the rhetorical structure of the text (Meyer and Wijekumar 2007).
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Empirical research on the effectiveness of reviews in tutorials has been limited (van der
Meij and van der Meij 2016a). A few studies on the contribution of text summaries to
recall reveal that text summaries can enhance retention for summarized content (Hartley
et al. 1976; Hartley and Trueman 1982; McLaughlin Cook 1981; Vezin et al. 1973).
Summaries presented before and after a text have been found equally effective.
Three initial experiments have been conducted to investigate whether reviews in a video
tutorial contribute to motivation and learning particularly how users could benefit from
reviews in different ways (Brar and van der Meij 2017; van der Meij and van der Meij
2016a, b). First, a review provides the user with a concise overview of the main issues or
events in a procedure, which can enhance retention and increase the user’s self-efficacy,
defined as the confidence in his or her capacity for task accomplishment. Second, a review
can serve as a frame of reference for the user’s own summary of a procedure. This feature
can also strengthen the user’s knowledge of the correct task solution and self-efficacy
belief. A third presumed benefit of a review is that it offers the user a second chance to
learn, compensating for any possible mind wandering during the presentation of a
demonstration.
Brar and van der Meij (2017) investigated a video tutorial that taught university student
how to conduct a t test using the SPSS software program. In the control condition, only
demonstrations could be viewed. In the experimental condition, a review was presented
after each demonstration. The study only assessed the contribution of reviews to learning
outcomes. The main finding was that review condition did better on both the knowledge
and performance test, but the difference between conditions was not statistically
significant.
van der Meij and van der Meij (2016a, b) also compared a demonstrations only control
condition to an experimental condition with demonstrations plus reviews. This research
was more similar to earlier studies both for the audience (i.e., upper elementary and/or
lower secondary school) and domain of the video tutorials (i.e., formatting tasks in
Microsoft Word). In the experiment where participants had unlimited access to the videos
during training, reviews enhanced self-efficacy (van der Meij and van der Meij 2016a). In
the study where participants had no control over video play, reviews were found to sig-
nificantly enhance task performance (van der Meij and van der Meij 2016b). Both studies
also found that learning was significantly higher in the review condition.
The present study further tests the effects of reviews in video tutorials on user moti-
vation and learning for formatting tasks in Microsoft Word. It differs from earlier research
in several ways. First, an important aspect neglected in the two earlier studies, which is
taken into account in the present study, is viewing behavior. When a review is added to a
demonstration video, the total length of the task video increases. This raises the question
whether users are willing to spend additional time viewing the review. Studies in which
data mining has been applied to determine drop-out rates for videos clearly show that video
length and viewing behavior are related (Guo et al. 2014; Wistia 2012). Their findings
indicate that shorter videos keep more users on-board and are viewed more thoroughly than
longer videos. In other words, data on viewing behavior can show whether reviews are
viewed thoroughly and whether this influences their effectiveness.
Second, the procedure of this study limited user control during training. Participants
could view the video as long as they wanted, and they could pause and replay sections as
they deemed necessary. However, access to the videos was blocked once they started to
practice. In effect, this procedure yielded an assessment of what was learned immediately
after viewing a video on a task (i.e., a training test). Third, previews were added to the
tutorial, which was expected to yield a pre-training effect. Because a slightly younger and
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presumably less knowledgeable audience was targeted, the previews were intended to
prevent overload problems when processing the demonstration and review (see Mayer and
Pilegard 2014). Fourth, a third condition was included. A new tutorial was created in which
a second, identical demonstration followed after the first demonstration. This 2-demo
condition controls for the possibility that the influence of reviews is mainly a repetition
effect.
Experimental design and research questions
The experiment was set up as a factorial design with a control condition (preview and
demonstration), and two experimental conditions (preview and demonstration and review,
and preview and demonstration and 2nd demonstration). The study aims to address the
following research questions.
Research question 1: How fully are the videos viewed?
Empirical research indicates that video length can have a significant effect on viewing
behavior. Longer videos often lead to a reduction in the percentage of a video that is
viewed (Guo et al. 2014; Wistia 2012). The videos in the present study differ in length.
Therefore, data are gathered about video coverage which is the percentage of a video that is
shown in play mode. These data give information about the possible role of video length.
Research question 2: How effective are the videos in increasing self-efficacy
and is there an effect of condition?
The video tutorials were designed to support motivation. For motivation we measure self-
efficacy which can be defined as a person’s expectancy for success on novel tasks (Bandura
1997). In line with the finding of an earlier study (van der Meij and van der Meij 2016a),
the increase in motivation is expected to be strongest for the review condition.
Research question 3: How well do the videos support learning and is there
an effect of condition?
Earlier studies with video tutorials for the same software tasks found that demonstrations
plus reviews increased learning more than demonstrations only (van der Meij and van der
Meij 2016a, b). This effect is also expected in the present study.
Method
Participants
The 65 participants in the study came from two fifth-grade and two sixth-grade classrooms
from an elementary school in the Netherlands. The mean age of the participants was
11.5 years with a standard deviation of 0.71. The 32 boys and 33 girls were randomly
assigned to condition after stratification for classroom. All participants were native
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speakers of Dutch. Therefore, all instructional materials, including the software, were in
Dutch.
Instructional materials
The videos in this study embodied a great number of instructional features from the
theoretical model. The tutorial taught six formatting tasks in Microsoft Word 2010. These
tasks were anchored in the participants’ task domain (M1 in Fig. 1) by starting with poorly
formatted original texts from school reports. The example documents were then changed
into well-formatted texts in the videos.
The videos in the tutorial were organized in a table of contents with (sub)titles. The first
chapter of the tutorial discussed adjusting the left and right margins for a whole document.
The second chapter revolved around formatting paragraphs, citations, and lists. The last
chapter dealt with the automatic creation of a table of contents.
The division of chapters and the videos therein represented a meaningful segmentation
(R1) of the various formatting tasks. The sequencing of the videos followed the simple-to-
complex principle (R3). For instance, the video on adjusting the left margin of a complete
document preceded the video on adjusting the right margin because it involved the easiest
manipulation of the screen object in both tasks.
For individual videos an upper limit of 3 min was chosen. Empirical research suggests
that this is a suitable length (M4) for maintaining user interest and preventing early drop-
out (Guo et al. 2014; Wistia 2012). Table 1 shows the length of the video types (1st and
2nd demonstrations have the same duration). The table gives the basic data for computing
the length of the video tutorials. Specifically, the length of the control tutorial is simply the
sum of all previews and demonstrations, and the length of the review tutorial is the sum of
all previews, demonstrations, and reviews. For the 2-demo tutorial the length is the sum of
all previews and the demonstrations taken twice. There was a considerable difference in
video length for the tutorials. The control tutorial lasts for 12.3 min, the review for
16.1 min, and the 2-demo tutorial is 20.5 min of video.
Table 1 Titles and duration (in s) of video types
Title Preview Demonstration Review
Adjusting the margins for the whole text
Adjusting the right margin 30 55 20
Adjusting the left margin 29 42 21
Adjusting the margins for a text segment
Indenting a citation to the left 34 45 22
Indenting a citation to the right 26 44 22
Indenting the first line of a paragraph 21 48 28
Improving a list 33 66 31
Creating an automatic table of contents
Styling the main headings 30 59 25
Styling the subheadings 21 75 35
Creating an automatic table of contents 30 43 21
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Participants could access the video tutorial via a website. The left-hand column of this
website presented the table of contents that was permanently visible on the screen. The
subtitles gave access to the videos. Clicking on a subtitle changed its color and opened the
video in the right-hand column of the website. The subtitle also appeared above the video.
There was no transcript of the narrative. The toolbar facilitated user control (A4). Students
could start, pause, stop, fast-forward and rewind the video with a toolbar. In addition, they
could adjust the sound level and switch between a full and partial screen representation.
The basic set-up of the videos was a combination of animated screen recordings with a
narrative spoken by a female native speaker. Three types of video were developed for each
task, namely, a preview, a demonstration, and a review. First and second demonstrations
were identical videos. The type of video that the users could expect to see was announced
in writing (e.g., ‘‘preview’’) in a slide that was displayed two seconds before its start. All of
the videos for a task automatically appeared one after the other.
In this study, pace (A3), the ongoing stream of information in a video, was measured as
the mean number of words-per-minute (wpm). The wpm count for all videos together
yielded a score of 118 wpm. Compared to a mean rate of 125–150 wpm for human speech
(Fulford 1992), this qualifies the pace of the videos as slow.
Previews (A2) prepared the user for the upcoming task by showing the start and end
state of a formatting task. In addition, previews explained and illustrated task-specific
concepts such as margins or paragraphs that the user may not yet know. Finally, previews
directed the user’s attention to pertinent screen objects and locations for task completion.
At the end of each preview there was a 2-second pause (R4). The preview was always the
first video that was displayed for a task. The mean length of a preview was 28 s (range
21–34).
Demonstrations showed and explained an unfolding scenario of task completion.
Research on paper tutorials for software training suggests that the construction of such a
scenario revolves around two key design decisions: (a) selecting a suitable solution method
and (b) concentrating on the most essential content (Carroll and van der Meij 1998; van der
Meij and Carroll 1998).
Software programs generally offer menu-based and key-based methods for task com-
pletion. For instance, to italicize a word in a Microsoft Word 2010 document in Windows
(it is different for the Mac), the user can select the I-object from the Font menu or press the
key combination Control ? I. The methods have a trade-off between simplicity and effi-
ciency. The recommended choice for novices or beginners is to teach only the simpler,
more insightful method (Renkl 2011, 2014; van der Meij and Carroll 1998). In software
training this is invariably a menu-based method.
The Four Components Model of procedural discourse for software indicates that tutorial
instructions generally consist of four main types of information: goals, interactions, pre-
requisites, and troubleshooting (van der Meij et al. 2003; van der Meij and Gellevij 2004).
Of these types, goals and interactions are a necessary component. Accordingly, mainly
information on goals and interactions was given.
Information about the goal serves the dual purpose of motivating and preparing the user.
It should identify what a task can accomplish and persuade the user to try to complete that
task. Information about the interactions couples the user actions with the program’s
reactions. The action component must tell the user how to act and what object to act on.
These action statements should be aligned to the user’s mental plan; they should follow the
path of the user’s thoughts and actions during task execution (Dixon 1982; Farkas 1999;
Zacks and Tversky 2003). The recommended, standard format for an action statement is a
succinct description built around an imperative verb (Farkas 1999). The reaction
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component should inform the user about the consequences of an action. This information
directs the user’s attention to interface changes (van der Meij and Gellevij 2004).
Each demonstration began with a display of the starting state of a Word document and a
narrative that introduced the formatting problem (e.g., ‘‘The left side or margin of this text
is too small’’, ‘‘This list does not look nice’’). Thereafter, the demonstration showed how
user actions led to changes on the interface. The narrative described these actions in
command form (e.g., ‘‘Click the left mouse button’’, ‘‘Drag the margin to 2.5 cm’’). The
narrative also regularly attended the user to screen objects, locations and changes using
standard phrases such as, ‘‘A window appears with the text…’’ and ‘‘You now see…’’. In
addition to this verbal signaling, visual techniques such as zooming-in and highlighting
were applied (A1). Statements about actions or interface states frequently included the
personal pronoun ‘‘you’’ to create a conversational style (M2). Demonstrations concluded
with a reminder of the accomplished goal of the procedure (e.g., ‘‘You can now see that all
chapter headings look the same. Word also knows exactly where they begin.’’). At the end
of each demonstration there was a 2-second pause (R4). In the 2-demo tutorial, the first
demonstration was always followed by a second, identical, task demonstration. The mean
length of a demonstration was 53 s (range 42–75).
Reviews (R5) summarized a procedure. They provided the user with a condensed ver-
sion of task execution. Reviews always appeared automatically after the demonstration for
a task, following a 2-second pause (R4). Reviews always began with the announcement
‘‘Remember’’. Thereafter, the narration concentrated on the task sequence and actions.
That is, the task completion scenario was emphasized by paying attention mainly to the
(sub)goals and user actions needed to achieve them. The narration was expressed in the
first person to model the personal action plan, and it used signal words to emphasize the
sequential nature of the actions (e.g., ‘‘First, I must select a chapter title. Next, from the
menu Styles I select Heading 1’’). The mean length of a review was 25 s (range 20–35).
A paper instruction booklet served to guide the participants through the process of video
viewing and practice. It described the sequence in which task videos were to be viewed,
and what practice file (see Procedure) to use in the training test.
Instruments
The initial self-efficacy questionnaire (ISEQ) was a paper-and-pencil instrument that
presented a screenshot of each of the six main training tasks and asks the question: ‘‘How
well do you think you can complete this task?’’. The same question was asked for each task
that was demonstrated in training. This tailored the measure of self-efficacy to the par-
ticular domain of interest (Bandura 2006). Answers were given on a 7-point Likert scale.
Following the advice from Hartley and Betts (2013), positive responses were placed to the
left. That is, the scale values ranged from very well (1) to very poorly (7). In presenting the
data, the scales are reversed, because that is easier to understand (i.e., a higher score
meaning greater self-efficacy). Reliability analysis using Cronbach’s alpha indicated sat-
isfactory results for initial self-efficacy (a = 0.73).
The final self-efficacy questionnaire (FSEQ) was a paper-and-pencil instrument that
asked participants to appraise their self-efficacy after training. There were three general
questions on ease of learning, and six questions about the formatting tasks (i.e., ‘‘I¨ can
change the left margin of a complete text’’, ‘‘I can change the right margin of a complete
text’’, ‘‘I can construct a nice table of contents’’, ‘‘I can present a nicely structured list’’, ‘‘I
can indent a citation on the right and left’’ and ‘‘I know how to indent the first line of a new
text segment’’). Because, the training tasks were familiar, the presentation format no longer
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was depicted but merely described. Only the data for the six formatting tasks are reported.
Scales and scoring were the same as for the ISEQ. Reliability analysis using Cronbach’s
alpha indicated good results for final self-efficacy (a = 0.87).
Both motivation questionnaires employed in the study had their origin in the Frage-
bogen Actuelle Motivation (Rheinberg et al. 2001). They were adapted for software
training, and used in earlier empirical studies (e.g., van der Meij and van der Meij
2014, 2015).
Five knowledge tests (i.e., pre-test, training, immediate post-test, delayed post-test, and
transfer test) assessed task performance. To ensure that participants understood the pre-test
items, task descriptions were coupled to screen shots displaying the start and end state. All
tests were performance tests with test tasks that had to be completed on the computer. Test
tasks used Word files specially prepared for the experiment. All files, except those in the
transfer test, included the same underlying problem demonstrated in the videos, differing
only in surface level features. Both the pre-test and training test presented one item at a
time. The post-tests presented all six test tasks simultaneously. This made these tests more
taxing than the training because participants were now facing the problem of selecting the
right method for a specific formatting task (compare Card et al. 1983). The transfer test
asked participants to solve four related but untrained tasks (e.g., change the upper margin
of a document).
Task performance on the tests was scored with the aid of a codebook. A score of 0
points was awarded for each task the participant did not complete correctly. Correct task
completion yielded a score of 1. Separate scores were computed for two training tasks that
required two separate subtasks (i.e., citations and list). This led to a maximum score of 8.
Scores were converted to a percentage of possible points. Reliability analyses, Cronbach’s
alpha, led to satisfactory results for all performance tests: pre-test (a = 0.60), training
(a = 0.67), immediate post-test (a = 0.74), delayed post-test (a = 0.73), and transfer test
(a = 0.76).
The study used a logging program as a proxy for viewing. For every second of video,
the program recorded the participant’s actions related to the video (i.e., playing, stopping,
pausing, or rewinding) and screen setting (i.e., full screen or partial screen display). With
the program, ‘coverage’ could be computed. Coverage was the number of video seconds
that were presented at least once in play mode. It was expressed as a percentage of the total
number of seconds in a video. For instance, when a participant’s log revealed that there
were 26 s of unique play events for a 28-s preview, the coverage for that preview was
computed to be 93% (26/28). The minimum score of 0% indicated that a video was never
set into play mode. The maximum score of 100% indicated that every unique video second
had been played at least once. Coverage was computed for all videos together (total
coverage) and for videos types (i.e., previews, 1st demonstrations, 2nd demonstrations, and
reviews).
Procedure
The study was conducted in three sessions held in the computer room at the school. All
sessions were led by the researcher. In the first session, participants were told that they
would engage in software training on Word to assist them in improving the formatting of
their school reports (5 min). Next, they were instructed to complete the ISEQ (5 min) and
pre-test (20 min).
Training followed a week later. This session started with a 10-min introduction that
explained Website navigation and video usage. Also the use of the instruction booklet was
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explained. Participants were instructed to view the task video until they felt sure they could
achieve the procedure. Thereafter, they could engage in practice on the task but they were
not allowed to look back to the video. The training included periods of practice (P1)
because production processes could not be directly supported by the videos themselves (see
Fig. 1). Practice on a task immediately followed the video for that task. This timing of
practice (P2) is beneficial for task execution during training. Practice was further supported
by practice files (P3) which kept distracting information to a minimum. Participants were
told to use headphones and work independently, and to call for assistance only when
needed. They were given 45 min of training time in the control condition and 50 min in the
experimental conditions to compensate for longer videos. [With one exception, this was
sufficient for all participants.] After training, there was a 10-min break, followed by the
FSEQ and the immediate post-test (20 min). Participants were not allowed to consult the
videos during testing.
The third session followed 1 week later. Participants first worked on the delayed post-
test (20 min). Next, the participants were informed about the transfer test, in which they
were to complete four new, untrained tasks (5 min). Then the transfer test was taken
(20 min).
Analysis
A check on the random distribution of participants across conditions revealed no signifi-
cant differences for age, F(2,62) = 0.28, p = 0.973, or gender, v2
(2,65) = 0.94,
p = 0.625. Conditions also did not differ on initial self-efficacy, F(2,61) = 0.14,
p = 0.873, or on pre-test scores, F(2,64) 1, n.s. There was also no effect of condition on
total training time, F(2,64) 1, n.s. The data set from two participants (one in the control
conditions, and one in the 2-demo condition) was incomplete. These participants were
included in the analyses whenever possible. AN(C)OVAs were computed to assess dif-
ferences in coverage, motivation and learning. For significant main results, contrasts were
computed using Tukey’s least significant difference (LSD). Initial checks for sphericity
violations (Mauchly) or assumptions of homogeneity of variance (Levene test) revealed no
significant differences. Tests were two-tailed with alpha set at 0.05. The degrees of free-
dom occasionally differ due to missing data. Cohen‘s (1988) d-statistic was used to report
effect size. These tend to be characterized as small for d = 0.2, medium for d = 0.5, and
large for d = 0.8.
Results
Video coverage
The mean total coverage was 70.2% (see Table 2). An ANOVA showed a main effect of
condition, F(2,62) = 6.49, p = 0.003. Post hoc analyses revealed that total coverage for
the 2-demo tutorial was lower than for the control (p = 0.001), and the review tutorial
(p = 0.041). The control and review tutorial did not differ for total coverage (p = 0.149).
A repeated measures ANOVA with condition as independent variable, and previews and
first demonstrations as the two measurement points, showed a significant decline over time,
F(1,62) = 76.8, p 0.001, d = 1.21. Coverage was lower for first demonstrations than for
123

previews. There was no main effect of condition, F(2,62) 1, and no interaction,
F(2,62) 1.
A repeated measures ANOVA comparing the two experimental conditions, with review
or second demonstration as a third time point, showed a significant main effect of the factor
of time, F(2,82) = 167.4, p 0.001. More importantly, there was a significant interaction
between condition and time, F(2,82) = 3.1, p = 0.05.
An ANCOVA comparing reviews and second demonstrations, with preview and first
demonstration coverage as covariates, indicated a significant effect of condition,
F(1,39) = 6.7, p = 0.013, d = 0.57. Table 2 shows that reviews yielded moderately
higher video coverage than second demonstrations.
Exploratory analyses of the factor of time (the sequence of nine task videos) for cov-
erage per video type revealed that previews yielded consistently high scores (range
89.8–97.7). Other video types displayed significant declines over time. The coverage for
demonstrations, reviews, and second demonstrations all dropped substantially as partici-
pants continued on in the video tutorial.
Self-efficacy
The initial scores for self-efficacy were slightly above the scale mean (see Table 3). A
repeated measures ANOVA with condition as independent variable and initial and final
self-efficacy reports as the two measurement points, showed a main effect of time. The
video tutorials enhanced self-efficacy significantly and substantially, F(1,61) = 90.02,
p 0.001, d = 1.48. There was no main effect of condition and no interaction between
time and condition, F 1.
Table 2 Means (standard deviations) for coverage by condition and video type
Condition Total Preview 1st demo Review 2nd demo
M (SD) M (SD) M (SD) M (SD) M (SD)
Control (n = 22) 79.8 (22.6) 92.0 (18.8) 70.2 (27.8) n.a. n.a.
Review (n = 21) 71.4 (16.0) 96.3 (7.5) 72.1 (22.0) 42.5 (30.0) n.a.
2-Demo (n = 22) 59.3 (17.4) 95.4 (9.8) 72.0 (21.5) n.a. 27.5 (22.2)
Total (n = 65) 70.2 (20.5) 94.5 (13.0) 71.4 (23.6) 42.5 (30.0) 27.5 (22.2)
Table 3 Means (standard devi-
ations) for self-efficacy (mean
scale value is 4; scale maximum
is 7. A higher score indicates
stronger self-efficacy) by
condition
Condition Self-efficacy
Before After
M (SD) M (SD)
Control (n = 21) 4.33 (1.51) 6.07 (1.19)
Review (n = 21) 4.22 (1.34) 6.33 (0.55)
2-Demo (n = 22) 4.43 (1.18) 6.05 (1.40)
Total (n = 64) 4.33 (1.33) 6.11 (1.11)
123

Learning
Table 4 shows the results for the test outcomes. The initial level of performance was low,
with a mean score of 11.7%. A repeated measures ANOVA with condition as the inde-
pendent variable and the regular task tests as four measurement points, showed a main
effect of time, F(3,183) = 202.74, p 0.001. Post hoc analyses revealed a significant
change from pre-test to training (p 0.000) with scores reaching an average of 79.7% (see
Table 4). There was also a significant change from training to immediate post-test
(p 0.001), with scores declining to 62.5%. Scores on the immediate and delayed post-
tests did not differ (p = 0.43). Also, there was no main effect of condition and no inter-
action between time and condition, F 1. Furthermore, an ANCOVA with condition as
the independent variable, pre-test score as the covariate and the transfer test as the
dependent variable, revealed no difference between conditions, F 1.
Discussion
The findings for coverage, a proxy for viewing, yielded an average of 70%. In other words,
more than two-thirds of each task video in the tutorials was shown in play mode and,
therefore, had the potential of being viewed by the participants. Video type affected this
outcome. Previews yielded coverage scores of well over 90%, while coverage dropped
significantly for the later parts of each task video. First demonstrations scored about 70%;
reviews and second demonstrations yielded scores of 42 and 27%, respectively.
One factor that appears to have had a negative effect on coverage is placement in the
tutorial. Whereas individual task videos stayed well within the 3-min limit recommended
by Guo et al. (2014), the total for the whole set of videos in the tutorial was considerably
longer, namely 12–20 min in the case of complete coverage (see ‘‘Instructional materials’’
under ‘‘Method’’). Exploratory analyses indicated that there was a decrease in coverage for
first demonstrations, second demonstrations, and reviews as participants got further along
in the tutorial.
Coverage may also have been negatively affected by redundancy. Although we tried to
optimize the design of each video type for the purpose(s) that it served, some overlap
between types for the same task was inevitable. The steep decline that occurred from
previews to first demonstration videos is perhaps a signal that participants found that the
latter video did not contain enough new information for them to keep viewing. They may
Table 4 Means (standard deviations) for test scores by condition and test
Condition Pre-test Training Immediate post-test Delayed post-test Transfer test
M (SD) M (SD) M (SD) M (SD) M (SD)
Control (n = 22) 9.7 (12.8) 76.1 (18.9) 58.5 (26.6) 55.1 (25.2) 33.0 (34.0)
Review (n = 21) 11.3 (15.3) 79.8 (22.5) 67.2 (26.9) 68.5 (25.8) 29.8 (36.8)
2-Demo (n = 21) 14.3 (19.1) 83.3 (19.5) 61.9 (29.7) 58.3 (25.7) 29.8 (35.0)
Total (n = 64) 11.7 (15.8) 79.7 (20.2) 62.5 (27.5) 60.6 (25.8) 30.9 (34.7)
123

have decided to drop out earlier with first demonstrations because they believed they had
already seen enough of what was needed for task execution in the preview.
Still, the distinction between preview, demonstration, and review videos is valuable
because each video type supports a different process in observational learning. This raises
the question how can videos be redesigned to yield higher coverage?
One possibility is to reduce the content of the previews. Currently, the previews prepare
participants cognitively and motivationally for the forthcoming demonstration by
informing them about the goal, the concept and the interface object(s) involved in task
achievement. Thus, the structure of previews may have given participants the false
impression that they presented a comprehensive view on task accomplishment. Perhaps
previews should concentrate on explaining only the concepts, just as in designs for the pre-
training principle (see Mayer and Pilegard 2014).
Another possible design solution is to use different examples. All videos for a task
featured the same sample file. This design choice was based on the consideration that an
identical example throughout a task case would free up cognitive space for attending to
other, more pertinent task features because familiar task aspects are more easily ignored
(Schnotz and Bannert 1999). Apparently, it did not work that way. Rather the presentation
of the same example may have given participants the impression that the content was
already known, which worked against continued viewing of all task videos. Akin to the
desirable differences hypothesis (see Yue et al. 2013), it is probably better to aim for a
design that makes participants perceive all video types for a task as slightly different.
One goal of the video tutorials was to provide motivational support to users. The
findings showed that the tutorials contributed significantly and substantially to self-efficacy
development. Participants indicated that the tutorials resulted in high final self-appraisals
of the capacity to accomplish the trained tasks in the future.
The gain in self-efficacy is relevant for future actions, as high self-efficacy has been
found to be related to trying harder and being more persistent with comparable task
challenges (Bandura 2012; Bandura and Locke 2003). More generally, the outcome is
relevant in view of the prominent place given to motivation in the theoretical model (see
Fig. 1), along with the motivational mediation assumption, which holds that motivational
factors mediate learning by increasing or decreasing cognitive engagement (Park et al.
2014).
Future studies might want to obtain a broader picture of the motivating qualities of
video tutorials by gathering the students’ opinion about aspects such as ease of use and
usefulness. The technology adoption model (e.g., Davis 1989; Davis et al. 1989; Joo et al.
2014) suggests that these appraisals can play an important role in the users’ willingness to
engage with video.
Another goal of the video tutorials was the provision of cognitive support. The data
showed that the tutorials effectively supported learning when assessment followed
immediately after the task videos. From a meager initial score of 12% of the items suc-
cessfully completed on the pre-test, the training test items yielded a score of 80%. Later
testing points revealed that there were still significant and substantial learning gains
compared to the starting level, but also that successful completion dropped to about 60%.
Compared to our first empirical study on video tutorials with and without reviews (van
der Meij and van der Meij 2016a, b), the learning outcomes are substantially lower on both
the immediate and delayed post-test, and the superiority of the review tutorial also failed to
replicate. An important difference with the present study lies in a situational variable (i.e.,
procedure). In the first experiment, participants could access the videos at all times during
123

training. In the present study, access was prohibited when participants worked on practice
tasks.
Why is the former more beneficial for learning? According to Bandura (1986), mod-
eling and production should be interleaved. One reason why participants need immediate
practice after observing a model is that it reveals where their imitation of the model fails.
When they cannot yet do what the model showed it can prompt participants to replay video
segments. Practice thus provides participants with a litmus test for how well a procedure
for task completion is understood and remembered, and also serves as a cue for where
retention failed. This, in turn, should be a strong stimulus for replaying (part of) the video.
In addition to addressing any gaps, replays can solidify the knowledge that has already
been acquired. The latter would appear to be especially important when subsequent videos
discuss closely related procedures.
The participants in the present study did well during practice (i.e., on the training test),
but their scores on the immediate and delayed post-test suggest that learning was fragile.
Blocking access to the videos may have affected consolidation. We had expected the
reviews to compensate for the lack of video access. The data showed that the scores on the
immediate and delayed post-test were about 10% higher than in the other conditions.
However, the difference was not statistically significant. The meager coverage for reviews
probably limited their impact.
Conclusion
The present study was conducted to further investigate the effectiveness of video tutorials
for software training that are designed according to a theoretical model that combines
insights from DBT (Grossman et al. 2013) and multimedia learning theory (e.g., Mayer
2014). The findings showed that the tutorials successfully supported and enhanced moti-
vation, but also that a lasting effect on learning was achieved only to a moderate degree.
One factor that probably negatively affected learning was the restriction imposed on
practice; this belongs with the ‘situational variables’ in the theoretical model. By blocking
access to the video during training tasks, the participants were limited in their opportunity
for learning.
In addition, the study investigated whether a video tutorial would be more effective if it
included reviews. The expected benefits for reviews were not found, which was ascribed to
their low coverage. One explanation that was advanced for the limited viewing of reviews
was tutorial length. Another factor that could have played a role concerned the content of
the reviews. Future studies might want to explore whether reviews achieve higher viewing
rates when the modeled task involves a (superficially) different example than in the
demonstration. Alternatively, it seems important to assess whether participants value
reviews. Because reviews are not commonly presented at the end of instructional videos it
seems important to gather the participants’ opinions about the usefulness of reviews.
Future research should also address the limitation that no process information was
gathered. Empirical research on signaling warns that effective support for a single
observational learning process (i.e., attention) does not necessarily yield greater learning
(de Koning et al. 2010; Kriz and Hegarty 2007; Skuballa et al. 2012). In other words, this
research suggests that it is desirable to obtain process measures for other activities involved
in observational learning as well. For instance, a think-aloud protocol during the practice
123

tasks or the post-tests might give information about the retention process when information
from the narrative is sought for, repeated, or summarized by the participants.
Acknowledgement The authors would like to thank the reviewers for their constructive comments on our
paper.
Compliance with ethical standards
Conflict of interest The authors declare that they have no conflict of interest.
Ethical approval A research proposal describing the study has been submitted to the ethics committee of
the University who has given approval.
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 Inter-
national License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution,
and reproduction in any medium, provided you give appropriate credit to the original author(s) and the
source, provide a link to the Creative Commons license, and indicate if changes were made.
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Hans van der Meij is Senior Researcher and Lecturer in Instructional Technology at the University of
Twente (The Netherlands). His research interests are: 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).
Jan van der Meij is Assistant Professor at the Department of ELAN Teacher Development and Director of
the teacher training institute of the University of Twente. He received his Ph.D. in 2007. His research
concentrates on functional use of ICT in education. This includes learning with (multiple) dynamic
representations, (live) video instruction, and video feedback coaching.
Tessa Voerman completed her M.A. study in the Learning Sciences at the University of Twente. She is
currently pursuing a M.A. study in Educational Science and Technology at the University of Twente.
Evert Duipmans completed his M.A. study in informatics at the University of Twente. He is currently
employed as a teacher at Saxion.
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