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This study focuses on the positioning of interactive questions within learning videos. It is attempted to show that the position of a question’s occurrence has an impact on the correctness rate of its answer and the learning success. As part of the study, the interactive learning videos in which the questions are placed are used as teaching materials with a class. The pupils have been working with the videos for around one month and some interesting results could be obtained. It is shown that questions which are asked too early in the videos are answered incorrectly more often than other questions. This manuscript also recommends an adequate positioning of the first question in learning videos. The new hypothesis that the length of intervals between popping up questions plays a minor role at rather short learning videos is constructed in this publication. Moreover, the positive impact on the long-term learning success of the participants of learning videos is determined.
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Smart Learning Environments
Wachtler et al. Smart Learning Environments (2016) 3:13
DOI 10.1186/s40561-016-0033-3
RESEARCH Open Access
An analysis of the use and effect of
questions in interactive learning-videos
Josef Wachtler*, Michael Hubmann, Helmut Zöhrer and Martin Ebner
Educational Technology - Graz
University of Technology,
Münzgrabenstraße 35A 8010 Graz,
This study focuses on the positioning of interactive questions within learning videos. It
is attempted to show that the position of a question’s occurrence has an impact on the
correctness rate of its answer and the learning success. As part of the study, the
interactive learning videos in which the questions are placed are used as teaching
materials with a class. The pupils have been working with the videos for around one
month and some interesting results could be obtained. It is shown that questions
which are asked too early in the videos are answered incorrectly more often than other
questions. This manuscript also recommends an adequate positioning of the first
question in learning videos. The new hypothesis that the length of intervals between
popping up questions plays a minor role at rather short learning videos is constructed
in this publication. Moreover, the positive impact on the long-term learning success of
the participants of learning videos is determined.
Keywords: Learning-videos, Interactive, Analysis, Questions, Positioning, Interval
length, Lazy-start, Tight-placed errors, Long-term success
The currently evolving trend of MOOCs (Massive Open Online Courses) leads to the
usage of videos for teaching, as a consequence (Khalil and Ebner 2013; Lackner et al.
2014). This means that learning-videos are making some kind of comeback because the
maxim “TV is easy and book is hard” (Salomon 1984) placed videos in a difficult position
for being used for the purpose of teaching. The mentioned maxim is motivated by the fact
that on the one hand the technical aspects of videos changed dramatically over the last
decades and on the other hand the role of the watchers is still more or less the same. This
to search for a video on the Internet and to watch it on many different (mobile) devices.
However, the activity of the watchers has not changed drastically which means that they
are still a passive audience.
These days videos are the most important digital media on the Internet (Lehner 2014).
The quality of videos is increasing, so creators need to think about new ways of standing
out (dpa 2015; Tembrink et al. 2013). One possibility is to include interactive compo-
nents. According to Lehner (2014) users on the Internet are used to interactions. They
do not want to watch videos passively and prefer interactive features inside a video and
being challenged throughout watching it. In the best case the user can influence what is
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happening in the video. Through the interactive components teachers also gain new edu-
cational opportunities, e.g. interactions may enhance the pupils’ motivation and impart
valuable media competences in addition to the syllabus.
In addition the quantity of information presented to students is huge. Different forms of
data is presented to them by using various amounts of text, colors, and shapes. It is logical
to assume that students can only process a limited number of information simultaneously
(Shiffrin and Gardner 1972) and due to that most of them is filtered out centrally (Moran
and Desimone 1985). Heinze et al. (1994) explained that a mechanism known as selective
attention is the most important part in human learning. As a consequence it is clear that
managing as well as supporting this attention enhances both, behavioral and neuronal
performance (Ebner et al. 2013; Spitzer et al. 1988)
As mentioned above it seems to be obvious that the nature of a video is passive and
based on this, it is clear that videos only have a consuming character. This indicates that
interaction as well as communication could be considered as major influencing factors
of the learning success because they are transforming passive watchers to active learners.
Due to this, it is important to offer different forms of interaction during a video and to
provide possibilities of communication in all forms and directions. Additionally, the inter-
action with the content of the video is of high importance. (Carr-Chellman and Duchastel
2000; Ebner and Holzinger 2003)
To address these influencing factors of learning success, a web-based information sys-
tem named LIVE (Live Interaction in Virtual learning Environments) first introduced by
Ebner et al. (2013) is developed (see Section Interactions in learning-videos and context).
It provides the possibility to enrich a video with different forms of interaction. A previous
study of Wachtler and Ebner (2015) observed that the approach is basically working if the
distribution of the interaction is well-balanced which means that the interactions should
be spread evenly across the video. This observation is based on some hypotheses. With
the current study we are going to prove the accuracy of the following of these hypotheses
based on short term as well as long term evaluations as suggested by Wachtler and Ebner
Lazy Start: the success rate of the first question is not very high
Tight-Placed Errors: the number of correct answers to the questions is decreasing if
they are placed too tightly one after another
With other words, the research problem addressed by this study could be summarized
to "analyzing the use and effects of interactive learning-videos".
As already mentioned, the used platform for interactive videos is explained after the
presentation of some related work (see Section Related work). After that, the accom-
plished study is explained before the results are pointed out and discussed (see Sections
Case study, Results and Discussion). Finally Section Outlook shows some research lim-
itations and after that a summary sums up the main parts of this work (see Section
Related work
This section lists different tools for providing interactive videos as a comparison to the
tool used at this study. Before that, this section presents some research work in the field of
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ARSs (Audience Response Systems) because the approach tries to support the attention
in face to face classroom situations in a similar way.
It is valid to assume that LIVE could be compared to an ARS. Such a system offers
the possibility to ask different forms of questions to the students in face to face class-
room situations (Haintz et al. 2014; Tobin 2005). The students are asked to answer these
questions by using a special handset or something similar. Furthermore an ARS usu-
ally offers powerful methods of analysis. It can be seen that this approach is comparable
to the used information system because LIVE places questions in learning videos to
transform passive watchers to active participants like an ARS in face to face classroom
Many studies regarding ARSs claim that such a tool has the power to improve the atten-
tion as well as the participation of the students (Ebner 2009). The study by Stowell and
Nelson (2007), for example, claims that with the help of an ARS the highest formal partic-
ipation could be reached in comparison to other classroom communication methods (e.g.
hand rising). This was also confirmed in a similar way by Cutrim (2008) as well as Latessa
and MD (2005).
Probably the best known possibility to enrich a video with interactions is to use the
built-in features of Youtube (YouTube 2016). These features are limited to textoverlays
and simple polls. Furthermore the possibilities of analysis are very basic only. The tool
named Zaption (Zaption 2016) offers a very wide range of possible interactions as for
instance multiple choice questions. The main drawback of this tool is that the time of
occurrence of the interactions is marked in the timeline of the video. This leads to the
problem that the students are able to jump from interaction to interaction without really
watching the video. Finally TEDEd (TEDEd 2016) is able to provide questions for videos
too. Unfortunately the questions are not related to a specific position in the video. They
are simply displayed together with the video and due to that it is possible to access them
during the whole video.
Interactions in learning-videos and context
This study uses the web based information system named LIVE to enrich learning-videos
with different methods of interaction and communication. LIVE offers the following
methods of interaction at both types of videos, on-demand and live broadcasting:
Simple questions
general questions which are not related to the content of the video
random and automatic
used to provide interactivity if there is no content-related question
a CAPTCHA is displayed in the same way and for the same reasons as the
simple questions
Ask teacher
students are able to ask a question to the teacher by using an offered text box
the teacher could answer per e-mail or by using an offered dialog
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Text-based questions
the teacher could ask text-based-questions to the students
at a live broadcasting of a lecture he can ask a question instantly by entering it
in a text box
at an on-demand video he can place the question at a specific position before
releasing the video
Multiple choice question
real multiple choice questions or true-false questions
the teacher could add these questions at pre-defined positions in the video
Report technical problem
students are able to report a technical problem
mainly used at live broadcastings of lectures if there are problems with the
video stream
Because LIVE is only available for registered and authenticated users there are three
different types of users, namely students, teachers and researchers. The students are only
able to watch the videos and to participate to the interactions. The screenshot in Fig. 1
shows LIVE while playing a learning-video (1) and the right sidebar (2) provides some
control elements to invoke interactions (e.g. asking a question to the teacher). If an inter-
action occurs, the video is paused and it is not possible to resume playing until the user
reacts to the interaction (see Fig. 2). In this case this means that the presented true-false
question has to be answered (Wachtler and Ebner 2014b).
In comparison to the students the teachers are additionally able to create interactive
videos and to analyze the performance of the students. During the process of creation
the teacher could select a video from various sources (e.g. Youtube) and enrich it with
interactions by selecting the methods to offer. For instance it is possible to add questions
at pre-defined positions in the video. This is done by selecting the position in the video
and by using a dialog to add the question there (Wachtler and Ebner 2014b).
Fig. 1 LIVE while playing a video. The video is displayed on the left (1) and some control elements to invoke
interactions are placed on the right (2)
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Fig. 2 Playing interrupted by an interaction. A true-false question is shown during a video
The analysis of the performance of the students consists of two parts. At first there
is a detailed recording of the watched time-spans to point out at which time a student
watched which part of the video (Wachtler and Ebner 2014a). As an overview the timeline
analysis draws a chart to indicate the number of users (green) and the number of views
(red) across the video (see Fig. 3). This could be used to identify the most interesting parts
of the video. To get more details it is possible to view a timeline for each student too. This
is shown by Fig. 4. It can be seen that a red bar marks each watched part of the video in
the timeline. If such a bar is hovered with the mouse the exact date and time is displayed
in relative and absolute values. The second part of the analysis are the results of the ques-
tions asked during the video. All questions are listed with the answers of the students.
Furthermore the correctness of the questions is displayed. It is clear that this is only pos-
sible automatically with multiple choice questions and not with text-based questions. For
the latter it is required to analyze them manually. As an example Fig. 5 shows the analysis
of the multiple choice questions. At the top there is the number of correct/wrong answers
Fig. 3 Timeline analysis. At the top the chart shows the number of users (green) and the number of views (red)
along the timeline of the video. Below that exact numbers are printed by moving the mouse across the chart
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Fig. 4 History analysis. For each user it is possible to view which part of the video was watched. For that a red
bar marks it in the timeline of the video. If the mouse is hovered over such a bar detailed information is
and below that the individual performance of each student is listed (Ebner et al. 2013;
Wachtler and Ebner 2014b).
Finally there are the users of a group called researches. Members of this group are
allowed to download all recorded data as a spreadsheet. This includes the following items:
watched timespans of each student
the number of users and views per second
answers to the different types of questions
In addition there are some lists containing the names of the videos or the texts of the
questions. These lists are needed for crossreferencing because the downloads mentioned
above are only stating the IDs of the videos or the questions.
The focus of the current study lies on the distribution of the questions at pre-defined
positions. This is done because it is important to know where to place these questions so
that they are supportive to the attention of the students.
Case study
In the course of this study, we are investigating the effects of learning-videos on the
learner’s success. The clear focus will be on the interactive component of the videos while
the position of testing questions within the videos plays a major part. As mentioned above
the following questions are explored: Does the time of occurrence of the first question
influence its answer’s correctness rate? The hypothesis of Wachtler and Ebner (2015),
which claims that the first answer has a higher trend of being wrong than the following
ones (Lazy Start), will be examined carefully. Moreover, a close look at a possible rela-
tion between the length of breaks between questions and the correctness of their answers
(Tight-Placed Errors) will be taken.
Fig. 5 Multiple choice questions analysis. For each multiple choice question the number of correct/wrong
answers is displayed. Below that a list of the students shows their answers to the questions
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Moreover, there will be an outlook on the long term success of the study in this
manuscript. It is measured with the results of a test which took place after half of the
videos had been watched. In order to enable comparability, the very same test was given
to students from another class who had been taught in a traditional manner. Both classes
have been at a comparable level before the study which is a necessary requirement for
speaking of possible comparability.
The test itself was constructed by a teacher who was neither involved in the production
of the videos nor in the traditional teaching of the second class. Thus, the exercises of
certain direction by inserting similar issues as in the teaching process. So, both classes
had the same initial position for this test.
Traditional teaching, so the way the class which does not watch the learning videos is
taught, means teacher-centered lessons where the pupils receive some direct input and
are mostly actively working at home. Should – or rather as soon as – they encounter
difficulties while solving problems, there is nobody there to give them a hint on how to
resolve problems.
Study environment
The survey was conducted in the subject of mathematics with a class of an academic
high school (BG Klusemann) which has an emphasis on STEM (Science-Technology-
Engineering-Math). The vast majority of the 20 students of this class are between 16 or
17 years of age. Furthermore, the attendance was compulsory. All the videos share the
main subject of differential calculus. Fifteen videos were produced for the study while only
seven have been used in class so far at the time of the writing process of this paper. They
cover all the required topics from the Austrian curriculum regarding differential calculus:
monotonicity, maxima and minima, inflection points, saddle points, finding polynomial
functions and the graphical construction of derivatives.
The learning videos are playing an important role in another study which deals with
the concept of flipped classroom (Loviscach 2013). One can already assume from the
concept’s name what this flipping of the classroom could mean: what is done at school in
traditional teaching becomes what is done at home and vice versa. So, the input phase –
watching the videos – is outsourced from the classroom and exercises, which used to be
homework, are shifted into classes.
In order to enable interactivity features in the videos, they are embedded in the platform
which is described in Section Interactions in learning-videos and context. The format of
the questions which pop up while watching the videos ranges from open questions over
true-false questions to multiple choice questions. They resemble the kind of questions
which are used in combination with ARS (Camuka and Peez 2014). Their application can
be divided into testing theoretical knowledge for true-false questions (see Fig. 6) and mul-
tiple choice questions (see Fig. 7) and testing practical understanding for open questions
(see Fig. 8) in the majority of cases. Due to a need for testing theoretical knowledge for
most cases, multiple choice questions outnumber the other formats.
Comparability of the results can of course only be achieved if there is a balance in the
complexity of the covered topics and the questions asked among all videos. Numerous
individual topics which are naturally regarded differently in difficulty by pupils are con-
tained in the collection of videos. Therefore, it has been attempted to distribute typically
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Fig. 6 True-false question. An example of an interactive true-false question in the learning environment
challenging topics to all videos in equal measure, respectively to compensate rather easy
with rather tough subjects. For instance, the usually demanding topic of functions and
their behavior at infinity, which requires abstract thinking, has been compensated with a
video about a topic the pupils have already been confronted with in a previous academic
year, namely the principles of extrema. Moreover, different videos which have a certain
interval length (see Section Setting of the questions) in common have been compensated
in terms of complexity among themselves wherever possible.
Setting of the questions
For the benefit of the learning success, the videos have been designed to be of minimal
length (Bergmann and Sams 2012). The average duration of approximately twelve minutes
for each video does not appropriately match the proposed length of intervals between the
interactive questions (Wachtler and Ebner 2015). The recommendations from aforesaid
paper had to be adapted.
The approach of setting a periodical interval length between occurring questions for
each video can be attributed to the recommendations for ARS from Martyn (2007) as
well. Therefore, it has already been well tested in a similar setting.
Interval lengths of 2, 4, 6 and 8 minutes, therefore step sizes of two minutes, have been
recommended. The videos used in this study are only approximately 12 minutes long,
while these in the study from Wachtler and Ebner (2015) are about 90 minutes long. Con-
sequently, due to total video lengths of about one eighth in comparison, the choices of
Fig. 7 Multiple choice question. An example of an interactive multiple choice question in the learning
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Fig. 8 Open question. An example of an interactive open question in the learning environment
interval lengths are drastically shortened. Reducing the interval lengths to exactly one
eighth would lead to an immensely high frequency of occurring interactive questions.
Thus, a compromise of setting the minimal interval between occurring questions to 90
seconds and increasing them by the step size of 30 seconds leading to the final intervals
of 1.5 minutes, 2 minutes, 2.5 minutes and 3 minutes was made. Eleven videos are taken
into account for this study which feature the following distribution of interval lengths:
1.5 minutes: used in 2 videos
2 minutes: used in 2 videos
2.5 minutes: used in 3 videos
3 minutes: used in 4 videos.
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In terms of the time of the first question pop-up, some adaptions were necessary as well:
they first appear after either one, two, three or four minutes. For the eleven videos that
are taken into account, the following distribution of times of the first occurring question
were chosen:
after 1 minute: used in 3 videos
after 2 minutes: used in 3 videos
after 3 minutes: used in 3 videos
after 4 minutes: used in 2 videos.
Data concerning different interval lengths
Due to the above listed interval lengths and the different total lengths of the videos, a
varying number of questions occurs. This circumstance resulted in the questions of the
videos which have an interval length of 1.5 minutes being answered correctly 86 times
and wrongly 34 times. Questions which occur in the interval of 2 minutes are answered
correctly 72 times and wrongly 53 times. A wrong-to-right distribution of 61 to 24 could
be observed at videos with an interval length of 2.5 minutes and videos with the longest
interval length were answered correctly in 48 and wrongly in 32 cases. In order to obtain
meaningful results, these wrong-to-right distributions per interval length are illustrated
as ratio in percent in Fig. 9.
Data concerning time of the first occurring question
With regard to finding a reasonable time of letting the first question pop up in the videos,
the above said starting points of 1, 2, 3 and 4 minutes are examined. Again, the number
of answers varies due to different numbers of viewers per video and the not-equally dis-
tributed classification of the videos. The answers of the first question with the earliest
occurrence were correct 29 times and wrong 24 times. Choosing to let the first ques-
tion appear after 2 minutes led to 16 right and 26 wrong answers. The first question
after 3 minutes showed a right-to-wrong distribution of 30 to 9 and the final obser-
vation of letting the first question arise after 4 minutes resulted in 13 correctly and 7
Fig. 9 Wrong-to-right ratio for videos of different interval lengths. The blue parts characterize the ratio of the
correctly and the orange parts the ratio of the incorrectly answered questions per video type in terms of their
interval length
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incorrectly answered questions. In favor of meaningfulness, the ratios of wrong vs. right
are illustrated in Fig. 10.
Contrast between first and remaining questions
The lazy-start theory includes the assumption that the first appearing question is
answered incorrectly more often than the further questions in general. For proving this
theory, the right-to-wrong ratio of all the first and all the remaining questions are deter-
mined and compared. The questions which are posted at the very beginning of the videos
resulted in 88 correct and 66 incorrect answers. All the other questions show an overall
right-to-wrong ratio of 309 to 161. An illustration of a transformation of these numbers
into percentages is seen in Fig. 11.
As in the other figures as well, the blue parts of the bars represents the share of
correct answers and the orange parts represent the share of incorrect answers. The
bars themselves stand for the first questions respectively all the other questions in the
Long-term effects of the learning videos on students
The long-term effects on the learning results of the students are measured via a test. It
was conducted approximately after half the videos had been released for the students’
availability. This test was planned independently from this study because tests are strictly
positioned in the Austrian national curriculum for schools. This led to the unfortunate
fact that not only the topics of the videos, namely differential calculus, but also some top-
ics which were dealt with before and which do not have a direct correlation to the relevant
issues, have been covered in the test. Thus, the test per se does not mirror the under-
standing of the topics from the videos a hundred percent. However, the predominant part
of the test deals with the topics from the videos which means that its results are therefore
clearly of importance for the actual learning effects of the videos on the pupils. More-
over, the exact same test was conducted in another class, which allows direct comparison
between the two classes. The other class has been taught in a conventional manner, mean-
ing via teacher-centered teaching in the classroom and homework exercises at home. The
distribution of grades, which leads from 1 being the best to 5 being the worst in the
Fig. 10 Wrong-to-right ratio of the first question. The blue parts characterize the ratio of the correctly and
the orange parts the ratio of the incorrectly answered questions per video type in terms of the time of the
occurrence of the first question
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Fig. 11 Comparison of the answers of the first and all further occurring questions. The blue parts characterize
the ratio of the correctly and the orange parts the ratio of the incorrectly answered questions for the first
appearing questions on the left and for all others on the right
Austrian school system, of the two classes which are compared in the study are seen in
Tabl e 1.
Discussion of the results of the first posed question / finding the optimal time of
appearance for the first question
First of all, the hypothesis that a questions shows a higher rate of being answered incor-
rectly if it occurs too early in a video is examined. Figure 10 reveals that a question which
arises after only one minute, so at about 8 % of the entire video duration, is answered
correctly in approximately 55 % of all cases. Starting after two minutes, meaning at
approximately 16 % of the total video duration, shows an even lower rate of success with
less than 40 %. These two attempts seem to be poorly effective.
The third attempt, posting the first question after three minutes, roughly at a quarter
of the video’s time, shows satisfactory results with the highest success rate of more than
three quarters. The latest occurrence - after one third of the video duration - of the first
question is slightly less successful again with almost two thirds of them being answered
Therefore, setting the first appearance of an interactive question too further at a
later time is not advisable due to a decrease in efficiency. The results of these ques-
tions are still noticeably better than the ones which pop up after approximately 8,
respectively 16 percent of the videos duration. Thus, it is recommended that the best
time for the first appearance of a question in interactive videos is after about 25 % of
its duration.
Table 1 A distribution of the grades in the two compared classes
Class A means the class which worked withe the concept of the flipped classroom and the learning videos and Class B means the
one which was taught in a traditional way
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In addition to the already shown first part of the lazy-start hypothesis which means
that setting the position of the first question’s appearance to approximately one quarter
of the video’s duration, the generally worse results of the very first question have to be
mentioned. This can clearly be illustrated by Fig. 11 which shows a comparison of the
right-to-wrong distributions of the first and the other questions. So, the correctness rate
increases in the course of the videos. That assumption is supported by the first question
being answered correctly in 58 % and all other questions in about 68 % of all cases.
However, when these results are computed in terms of statistical significance, it is by far
not improbable enough that the first answers may only be incorrect more often acciden-
tally. The standardly calculated p-value of 0.37 (t=0.907, df =20) speaks for itself. Still,
there is a tendency towards the hypothesis that the first question is generally answered
incorrectly more often than all others, but it is not significant. Thus, some further inves-
tigation of this distinct research question would be necessary to obtain satisfactory and
relevant results. A future study with a larger number of videos could give some indica-
tion of whether a question being in first position or not is crucial for its right-to-wrong
ratio. One possible reason for the weak start might be a lack of concentration at the very
beginning. Moreover, the videos are designed to function as homework assignments and
for usual, only one video is part of the preparation for a lesson. An exact exploration of
the reasons will be made at the end of the practical part of the survey with the aid of
Discussion of the results of different interval lengths between questions
The “tight-placed errors”-hypothesis, which claims that questions after a short inter-
val between appearing questions are more likely to be answered correctly, could not be
verified. Figure 9 indicates that an interval length of 1.5 minutes leads to a relatively satis-
factory rate of approximately 71 % of correct answers. In the case of an interval length of
2 minutes, about 58 % of all questions could be answered correctly by the students. The
very best value, if only just, was achieved at an interval length of 2.5 minutes with 72 % of
right answers. The longest interval length, namely 3 minutes showed respectable rates of
correctness with an average of 65 % of all questions.
One can notice that there cannot be any obvious tendency observed. The values of 2.5
respectively 1.5 minutes exhibited the highest success rates but are separated by a lower
rate at 2 minutes. Thus there is no real trend discernible and all the tested videos show a
vaguely similar rate of correct answers. All in all, it can be said that all the interval lengths
lead to adequate results and would be suitable for videos of a similar length to the ones
used in our study. This observation might be resolved by the relative short lengths of the
videos in comparison to the ones used by Wachtler and Ebner (2015).
So, we construct the new hypothesis that the interval length between appearing ques-
tions in videos of a length of up to around 20 minutes is rather irrelevant. These kinds of
videos show similar success rates for all interval lengths. The relevance of having a closer
look at the pauses between questions increases with the lengths of the videos.
Discussion of the long-term effects of the learning videos on students
The results of the test which was conducted in the class that has been taught with the con-
cept of the flipped classroom and with the aid of the learning videos show a satisfactory
distribution of grades with a mean and median of 3 and a standard deviation of 1.247.
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Wachtler et al. Smart Learning Environments (2016) 3:13 Page 14 of 16
In the class which dealt as a means for comparing the results and which was taught in
a conventional way, the very same test led to considerably worse results. This class had a
distribution tending to negative results with a mean of 3.948, a median of 4 and a standard
deviation of 1.026.
When considering statistical testing for the hypothesis that the first class – the
one taught with the learning videos – achieves better results than the other class,
statistical significance leads to a p-value of approximately 0.014 (with t=2.573,
df =37). This value is clearly below the standard significance level of 0.05. The
result clearly proves the better performance of the class which received their input via
the learning videos in opposition to traditional teaching methods. In the class which
watched the videos, two students managed to gain the highest grade, while no stu-
dent succeeded in the same in the other class. Eight of the nineteen students from
the latter got the worst grade there is in the Austrian school system, whereas only
four of the twenty students from the class which used the learning videos failed the
This shows that the teaching method applied for this study has a definite positive
influence on the students’ selective attention and therefore on the long-term success
because of a clearly better performance in comparison with students who have not
watched the videos and because of the satisfactory distribution of grades within the
In order to attain some more expressive results when it comes to the "tight-placed errors"
hypothesis, one would at least have to enlarge the study group or observe the behavior
of the success rate with a higher number of videos per interval length. For that, the same
interval lengths as presented in the Section Case study would be a good choice for videos
of a similar length.
Moreover, one should further investigate on the created hypothesis that the impact
of the interval length between appearing questions on shorter videos is not as high
as same on longer videos. It is further recommended that videos with lengths of 30,
45 and 60 minutes are taken into account as well, in order to being able to find out
from which video length onward the interval length becomes relevant for the cor-
rectness of the answers. Obviously, the respective interval lengths have to be adapted
to the lengths because the number of appearing questions would simply become too
The long-term effect on students deserves to be observed more closely as well because
the test in the middle of the study which contained some independent topics is not an
entirely convincing source. A recommendation would be some testing after the topic
has been completed and all the videos have been watched. Of course, no other topics
should be included in this testing process. Furthermore, some group which has been
taught in a traditional manner and can be used for a suitable comparison would also
be needed. In the optimal case we recommend one group which has been taught in
a traditional manner, one group which has been taught by traditional videos without
interactions and one group which has been taught by videos with interactive compo-
nents. This would facilitate the analysis of how success is dependent on interactive
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Wachtler et al. Smart Learning Environments (2016) 3:13 Page 15 of 16
This study deals with the application of interactive videos in math classes. For that sev-
eral learning videos were created and enriched with different interactive questions. The
distribution of the questions is based on some hypotheses identified by a previous study
of Wachtler and Ebner (2015). With the current study the accuracy of these hypotheses is
examined by taking short term as well as long term evaluations into account.
Based on the evaluation of the first hypothesis it is shown that too early appearing ques-
tions are prone to be answered incorrectly. Thus, it is advised to wait patiently until the
first question pops up. At around one quarter of the entire video length has proven to be
an adequate time for the first interactive question.
Apart from that, the hypothesis which claims that questions show a higher incorrect-
ness rate when they are placed too densely one after another has been examined. This
hypothesis, however, could not be confirmed in this work. The interval lengths between
questions does not correlate with the correctness of their answers in the kinds of videos
which were regarded for this study. So, the assumption that the distances between ques-
tions only have an impact on longer videos was made. A future work could deal with this
new hypothesis.
Generally positive long-term results have been achieved throughout this study. These
have been examined by a direct comparison between one class that has worked with the
videos and one that has experienced conventional teaching methods. The first managed
to obtain remarkably better results. It is important to return to the issue of long-term
results in a future work with customized testing material which merely includes the topics
relevant for the videos.
Based on these results the research question (see Section Introduction) is finally
ARS, audience response system; CAPTCHA, completely automated public turing test to tell computers and humans
apart; LIVE, live interaction in virtual learning environments; MOOC, massive open online course; STEM,
Competing interests
The authors declare that they have no competing interests.
Received: 21 December 2015 Accepted: 20 June 2016
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... The previous studies (Pandey, 2018;Sauli, Cattaneo, & Van der Meij, 2018;Wachtler, Scherz, & Ebner, 2018;Wachtler, Hubmann, Zohrer, et. al, 2016;Petan, et. al., 2014) have revealed a considerable number of the characteristics distinguishing the interactive video as follows: ...
... . However, among challenges that emerge while using the interactive videos as the main content is how to make learning more interactive and less negative? Researchers who have studied learning through interactive videos have defined interaction in relatively different ways. Still, with regard to most of the previous studies (Shelton, et. al., 2016;Wachtler, et. al, 2016;Delen, et. al., 2014;Merkt & Schwan 2014), it can be stated that the interactive video includes many forms for designing interaction as shown below: ...
... training setting, namely its capacity to enhance student's interest and make learning more pleasant for them. (Bajrami & Ismaili, 2016). Interactive videos where questions pop up during the video have been shown to have a positive effect on students' grades long-term, with the short-term effect dependent on the timing of questions during the video (Wachtler et. al, 2016). ...
Technical Report
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This guide provides practical instructions and advice on how to organize digital competence training for language teachers. The recommendations included in the guide are derived from research and experience of developing and organizing a series of training events for language teachers by the authors of the guide. This guide is developed primarily for teacher trainers who work in language education. The guide can also be useful for language teachers who wish to develop their digital competence and better employ digital technologies in their teaching practice. The current guide is the capstone of a series of training events that involve presentations on the latest trends, new ideas and innovative teaching techniques. The training events provide opportunities for peer-to-peer interaction and involve a series of workshops and teaching experiences in which practical proposals are demonstrated, as well as new technological and methodological developments in the field of second/foreign language. This trainer guide is composed of three parts. Part A presents an overview of training methodologies for language learning in face-to-face, online, and blended formats. Part B includes a framework model for teacher training developed based on the experience from two series of webinars. Part C incorporates a collection of 15 teacher training modules, fully described and available as OERs. The language teacher training experience and research summarized in this guide were undertaken in the frame of the project: Digital Competences for Language Teachers (DC4LT This project has received funding from the European Union’s Erasmus Plus programme, grant agreement 2018-1-NO01-KA203-038837.
... This result was supported by some previous studies. Wachtler et al [32] stated that the interactive component in learning media could gain the interaction that may enhance students' motivation. This interaction could be considered a major influencing factor in learning because it could transform the passive watchers to become active learners. ...
... There have been several approaches to increase student engagement in VBL, such as embedding annotation tools, quizzes, learning resource recommendations and visual learning analytics (Chatti et al., 2016;Giannakos, Sampson, & Kidziński, 2016;Schulten, Manske, Langner-Thiele, & Hoppe, 2020;Wachtler, Hubmann, Zöhrer, & Ebner, 2016). There are also collaborative tools integrated into VBL, such as forums and ratings (Chen, Gao, Yuan, & Tang, 2019;Okumoto, Yoshida, Umemura, & Ichikawa, 2018), to increase engagement by social interaction and knowledge sharing. ...
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... Through the inclusion of interactive elements in videos, users are able to interact with the video content as well as with the developer and with other users during the learning process. With interactive video, the individual is no longer a passive viewer (Wachtler et al., 2016), but is able to direct the process and communicate with others (Geri et al., 2017). This innovative type of video was first introduced into distance-learning platforms with the aim of increasing interactivity during the learning process (Cherrett et al., 2009;Schwan & Riempp, 2004). ...
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... A number of approaches have investigated ways of integrating interactive elements to increase learner engagement with videos. One of the proven strategies to increase engagement with videos is in-video quizzes (Giannakos, Sampson and Kidziński, 2016;Kleftodimos and Evangelidis, 2016;Kovacs, 2016;Wachtler et al., 2016). It has been shown that in-video quizzes increase engagement with videos but may also lead to learners skipping key points to focus just on answering the quizzes (c.f. ...
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... The level of the students' understanding of the new topics can be easily assessed, for example, through scoring specially designed written tests, but assessing the gained practical skills is a quite multidimensional task [46]. Data, derived from the participation of students in educational research, are a powerful tool to researchers as they can utilize them to identify hidden patterns by using analytics techniques [15,16,27,33,41,61,63,65]. This study is initially based on the assumption that the effective completion of all the steps comprised an experiment, is a robust indicator that the learner has a high perception of the lab environment and has also acquired all the necessary hands-on skills. ...
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It is clear that a system known as selective attention is the most crucial resource for human learning (Heinze et al. 1994). Due to this fact a web based information system is developed to support the attention of the watchers of a learning video. This is done by enriching the video with different forms of interactions. Among others there are interactions presenting multiple-choice questions at predefined positions in the video as well as randomly occurring interactions displaying general questions, which are not content related. To gain a basic plan which points out how to distribute the interactions over the video the usage of the information system at a lecture is analyzed. For that on the one hand some feedback of the users is provided and on the other hand an objective analysis of the results of the multiple-choice questions is done by evaluating their time of occurrence in the video.
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In general videos have a more or less consuming character without any interaction possibilities. Due to this fact a web-based application is developed which offers different methods of communication and interaction to a certain learning-video. This should help attendees to avoid that they become tired and annoyed. The lecturer is able to use interactions to omit whether learners are able to understand the content of the video. For instance the developed web-application offers the possibility to add multiple-choice-questions at predefined positions. Furthermore there are many different kind of analysis as for example a detailed attention-profile. In this publication the implementation of a first prototype is described as well as a first field study which points out that learners? interactions and engagements increased arbitrarily.
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Due to the fact that students' attention is the most crucial resource in a high-quality course it is from high importance to control and analyze it. This could be done by using the interaction and the communication because they are known as valuable influencing factors of the attention. In this publication we introduce a web-based information system which implements an attention-profiling algorithm for learningvideos as well as live-broadcastings of lectures. For that different methods of interaction are offered and analyzed. The evaluation points out that the attention profiling algorithm delivers realistic values.
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Human learning processes are strongly depending on attention of each single learner. Due to this fact any measurement helping to increase students' attention is from high importance. Till now there are some developments called Audience-Response-Systems only available for face-to-face education even for masses. In this publication we introduce a web-based information system which is also usable for online-systems. Students' attention will be conserved based on different interaction forms during the live stream of a lecture. The evaluation pointed out that the system helps to enlarge the attention of each single participant.
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Massive Open Online Courses, shortly MOOCs, are a trending phenomenon in online education. Neither distance education nor online courses are new, but especially in the field of technology enhanced learning, MOOCs have been gathering enormous attention by the public. Thus, following the main idea of bringing education to a broad range of people, two universities in Graz developed an xMOOC platform for the German speaking area, mostly addressing people in Austria. Before the first courses started the authors reflected on how such a MOOC should be carried out and which key factors (didactical, technical and administrative) have to be considered. This research study strongly concentrates on developing a checklist for practitioners who would like to do an xMOOC in the future by examining different xMOOCs and reflecting first experiences gathered through daily work on MOOCs. It can be concluded that doing a Massive Open Online Course is much more challenging as maybe expected at first sight. Nevertheless the proposed checklist will help to overcome first barriers and provide solid steps towards one’s first online course.
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Question-driven Audience Response Systems (ARSs) are in the focus of research since the 1960s. Since then, the technology has changed and therefore systems have evolved too. This work is about conception and implementation of the web-based ARS RealFeedback which uses the principle of bring your own device (BYOD). A state-of-the-art analysis compares the features of existing web-based ARSs. The most important findings are used for the conception and the implementation of the system. Thinking-aloud tests, and the first usages during lectures confirm that the chosen requirements are very significant and valuable for lecturers
Full-text available
Web 2.0 technologies pervade our daily life as well as educational settings. A fairly new approach is communication through so called microblogging channels. Mobile devices with Internet access can be used to send short messages from a microblog. Combined with social network environments, applications such as Twitter, Jaiku, Pownce, and Plurk enrich our ways of communication. At Graz University of Technology (TU Graz) some research work has been done to investigate using microblogging tools to improve face-to-face lectures. The study described in this paper took place at a large international conference on e-learning, where a Twitter channel was established for discussion among the participants of the conference and those from outside. This stream was also used to “tweet” (post on Twitter) statements during the keynote presentations. By viewing the tweet-channel via an additional projector, the audience was able to follow the live-blogging session synchronously to the ongoing speech.
Der Einsatz von Videos in eLearning-Applikationen wird zunehmendforciert. Es istdavon auszugehen, dass im Internet zukünftig die Bedeutung der Videotechnologie sogar noch zunehmen und der Interaktivität dabei eine besondere Rolle zukommen wird. Die Interaktivität in videogestützten eLearning-Anwendungen wird derzeit noch wenig genutzt, obwohl dadurch ein exploratives, situiertes und problemorientiertes Lernen gut unterstützt werden kann. Der Nutzer eines interaktiven Videos (auch als »Hypervideo«, »dynamisches Video« oder »clickable Video« bezeichnet) kann sich, ähnlich wie beim hypertextbasierten Lernen, die für ihn relevanten Informationen mithilfe der interaktiven Funktionen heraussuchen und je nach verwendeten Interaktionsele-menten auch aktiv mit dem Video arbeiten. Dieser Beitragführt kurz in die Technologien und die besonderen Herausforderungen ein, die mit der Erstellung interaktiver Videos verbunden sind, und bietet einen Überblick über die aktuelle Verbreitung und Nutzung interaktiver Videos im Bereich eLearning. Darauf aufbauend wird ein neu entwickeltes Tool zur Realisierung interaktiver Videos vorgestellt und es werden erste Erfahrungen in der Unterrichtsanwendung präsentiert.