情報処理学会 インタラクション 2020
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A Tool to Transform Monologue Lecture Style into Dialogue Style byAdding a Tutee Agent in an Educational VideoAri Nugraha†1Izhar Almizan Wahono†1

Tomoyuki Harada†1Tomoo Inoue†2

Abstract：One interesting finding regarding lecture videos is that watching dialogue-style lecture videos produce better learning
results for observer students than the monologue ones. Previous studies found dialogue-style lecture videos are better thanmonologue lecture videos because the observer student learns more from tutee than a tutor. Inspired by how the tutee plays a rolein a dialogue video, we developed a system that transforms a monologue-style lecture video into dialogue-style lecture video byadding a tutee agent. As the result of the experiment of the system, most observer students preferred the dialogue style videos forvarious reasons.

based on MOOC's engagements dataset. They found that shorter

1. Introduction

videos duration from few seconds to 6 minutes have higher

The majority of lecture videos provided in an online
environment

suchasMOOCs,

Open

Courseware,

engagement than videos with duration more than 6 minutes.

andLong lecture video duration tends to increase cognitive load ofvideo-sharing platforms, are delivered in monologue style wherestudents, to reduce this, one of the strategies is to break the

one lecture/tutor presented the learning material [1]. Previous

contents into smaller chunks of segments or segmentation.

studies [1,2] found that dialogue observers student performing

Breaking the learning content into smaller chunks of unit isbetter than those given a monologue video, one of the reasons iscalled micro-learning, and it refers to learning processes cover athe observers or students can learn as the tutee in the dialogue

timespan from a few seconds to 15 minutes or more [6].

videos. Motivated by the tutee’s role in dialogue video, in thisstudy we proposed a system to enhance monologue style lecture
video into dialogue-like style video to increase observer
students learning performance and their attention spans when
watching the lecture video.

2. Related Works
2.1 Video as a Learning Resource
Videos are still the primary resource of learning material indistance electronic education, particularly in MOOCs platforms.
Popular MOOC platform such as Coursera, edX, Udacity, andKhan Academy made lecture videos as their main central course

Figure 1. Workflow of Monologue to Dialogue Video
Transformation

activity [3].
Student interaction with video material in MOOC platform havebeen explored by several studies. A large-scale study on videointeraction patterns found that a high number of video replay
and pause indicates a significantly higher perceived video
difficulty [4]. Other study explored optimization of videointerface such as providing preview or thumbnail of video parts
where many learners tend to be interacted most [5].
Lecture video duration is also one of the topics explored byresearchers in educational technology. One of the examples ofthis is empirical study conducted by Guo, Kim, and Rubin [6]†1 Graduate School of Library, Information and Media Studies, University ofTsukuba, Japan†2 Faculty of Library, Information and Media Studies, University of Tsukuba,Japan© 2020 Information Processing Society of Japan

2.2 Learning Video Enhancement
As we mentioned before, segmentation can be used to break thelecture content into several segments. Short videos proven tohave positive effect on learning outcomes, as study shown thatlearners in segmented groups have significantly better learning
outcomes than in non-segmented group [7].
Recent study confirmed more on the effect of segmentation inprocedural learning, where learners in the segmented interactive
video group were better at performing the procedure thanlearners

innoninteractive

video

groups[8].

Learning

segmentation is not always producing positive effect to thelearning process, like a too many segments are found to be1109

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annoying and inappropriate [9]. Still in regard to segmentation,

in web-based environment.

there are also exists studies related to automatically segments

The tutee is embedded into the video dynamically using HTML5

the lecture video, such as by analyzing the content of theVideo API and JavaScript, in the form of an animated image andsynchronized slides using OCR [10] and analyze the lecture

placed on the layer above the lecture video.

slides/presentation for any subtopic border such as title slide.
In-video quizzes, a small test which appears in the middle ofvideo helps learners recall recently learned lessons [11]. A study
found that in-video quizzes were successful in creating anengaging and interactive mode of content delivery [12].
Making annotation at a specific time point of the video whereimportant concepts occur [13] also have been studied, as it isplaces minimal demands on the working memory and reduces
disruption to the lecture as the student doesn’t have to watch theFigure 2. Tutee agent annotation interface

entire video again [14]. Another type of marking specific scenes
on video similar to annotation in the video have been explored.

As seen in Figure 1, teacher or course creator needs to annotate

Researchers applied keyword tagging concept combined bytheir monologue video first using our annotation interface. Thegamification [15] to increase engagement. The that study, theannotated texts created from the annotation interface by teacher

participants tagging specific scenes on the video with keyword

are automatically converted into tutee agent dialogue, played atand got rewarded for their contribution.

the designated time when the video is played. While the tutee

2.3 Observational Learning

agent is speaking, the other part of the video will be paused to

Observational learning, or observing learning activities carried

mimic a dialogue between a tutee and a tutor.

out by others, such as observing dialogue between tutor andtutee proven to be better than learning by only observing tutor
alone [1, 2]. An observer student, student who watch the videointeraction between tutor and tutee, can master how to performthe activities without overt practice or direct incentives [16].
Several reasons found why dialogue-video better are, such as
such as dialogue-observers pay more attention to what the tutees
said than to what the tutors said, and tutees can serve as a modelof learning [1].

Figure 3. Monologue video enhanced into dialogue-style with aObservational learning not only effective with human to humantutee agent.

tutoring, it is also found that overhearing dialogue between
virtual tutor and virtual tutee in virtual tutoring sessions have

3.3 Hypothesis

positives effects to observer student, such as student asked

Our hypothesis in this study is the observer students watchingsignificantly more deep-level reasoning questions [17], and they

our tutee agent added lecture video will produce better learning

can produce more relevant propositions in free recall questions

performance than the observer students watching the monologue[18].

lecture video.

3. Proposal

4. Initial Evaluation

3.1 System Design

4.1 Method

Inspired by previous studies on observational learning, learning

For the evaluation, we conducted a within-subject experimentsegmentation and virtual tutoring sessions, in this study we wantinvolving 12 participants as an observer student with no priorexplore how virtual tutee agent could improve existing

experiences in using MOOC and unfamiliarity with the theme inmonologue video. Figure 1 visualized our system design

the videos. Two conditions, Monologue (MON) and Dialogue

workflow.

with Tutee Agent (DIA) was used in this experiment. To

3.2 Implementation

counterbalance the effect of such as fatigue, learning effect, orTo implement our proposed design, we developed our systembias from the learning style, Latin square design is used to makewhich enables us to embed an avatar of tutee agent inside video

the order of the condition and the lecture video theme as shown© 2020 Information Processing Society of Japan1110

情報処理学会 インタラクション 2020
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4.3 Results
4.3.1 Learning Gain
Table 1. Experiment Conditions

MON Condition
DIA Condition

Lecture video themes
ID (Length)
MD (Length)
MON_ID (14:44)
MON_MD (13:28)
DIA_ID (16:45)
DIA_MD (15:50)

As for the lecture videos, we produced two lecture videos in twothemes, Interaction Design (ID) and Metadata (MD). The lengthof videos is similar, 14:44 minutes for ID theme and 13:28 forMD theme. All the dialogue of the tutor and the tutee agent
inside the video are scripted. We used the talking-head style

Figure 4. Means of propositions (N=12)

with slide for the video lecture-style, as it is proven to havebetter learning performance than other lecture-style [20]. We

Figure 4 shows that DIA condition could produce better number

also used a different presentation slide style for each theme,of relevant propositions and smaller number of irrelevant

where the ID theme contains more texts and explanations inpropositions than MON condition. Learning result for eacheach slide than the MD theme. And as for the dialogue styletheme was also consistent with the overall learning gain result invideo, we used our system annotation interface to produce theFigure 4., where DIA produced better relevant propositions thanvideos by annotating the tutee agent to the monologue video. We

MON in each theme.

designed the tutee agent role in the video as a summarizer andrepeater of what the tutor said, where the tutee agent will do it atTable 3. Means of relevant propositions for each video theme,

the end of each slide in the video like the example in Table 2.

MD (N=6) and ID (N=6)
MDIDMSDMSDDIA

3.17

2.64

3.67

1.97

MON

2.67

2.66

2

2.45

Table 2. Example of tutee dialogue at the end of the slide in ID
theme.
Tutor

Tutee

“... For this second goal we need to take into account:
Who the users are; What activities are being carriedout; Where interaction is taking place...”At the end of current slide, before presentation moving
to the next slide“So first we need to know the users are, second know
their activities, and know where the interaction istaking place at”

4.3.2 Subjective Rating on Experience
As we have mentioned before, we used questionnaire afterparticipants finished watching each video and answering the freerecall test for the subjective rating on the participant experience
when watching the lecture video. The results presented in Figure

4.2 Measurements
We measured several variables for this evaluation: learning gainby the number of relevant propositions from observer student’s
free recall/post-test quiz answer sheet (6 deep question for eachtheme), and observer’s subjective rating on learning experienceby questionnaire based on UES-SF [21] with 5 points Likert’s

5. showed that DIA could produce better user experience thanMON, in all aspects except in the video difficulty, where DIA
and MON gained the same rating with 2.5 out 5. These findings
indicate that dialogue style (DIA) videos are more enjoyable,
boosted confidence about the material, promoted focus attention,and more attractive than monologue style (MON) videos.

scale ranging from strongly disagree to strongly agree for theanswer.

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our dialogue-like lecture video with the tutee agent could
produce better learning and user experience than the monologue
video.

References[1]

Figure 5. Means of subjective rating items
4.3.3 Qualitative Data
We gathered an interesting insight about what the participant’s
lecture style preferences and the reasons behind it frominterview data. Eight (8) participants prefer dialogue style video,
where three (3) participants prefer monologue style video, andone (1) participant does not have any preference for the lecture
video style. The reasons for those participants who preferdialogue style video are mainly because of the role of tutee
agent as a summarizer of tutor’s explanation like what P2 andP11 said in the interview, which in line with what intended for inthis study.
“I found it easier for me to understand the video since the, there
is an interactive dialogue in it, and also the lady (tutee agent)
here, she said the term or the materials in the simple ways.
Which I think, I found it useful for me...” [P2].
“The animated agent help to summarize what the lecturersays, so I can memorize better about the key point in the lecture,each of the subtopics, or sublecture (subtopic) of the wholelecture...” [P11].

5. Conclusion
Inspired by the benefits offered by dialogue style learning video,
we propose a system which turns monologue video into a
dialogue-like video by adding tutee agent to the monologue
video. For evaluation we conducted experiments involving
observer students to watch our dialogue-like and monologue
video. Based on the data collected from free recall tests,
questionnaires, and interviews with participants, we found that© 2020 Information Processing Society of Japan

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