Grouping System to Promote Collaborative Historical Analogy

Ryohei Ikejiri
The University of Tokyo
ikejiri@iii.u-tokyo.ac.jp

Ryo Yoshikawa
Nagoya Bunri University
yoshikawa.ryo@nagoya-bunri.ac.jp

Yasunobu Sumikawa
Tokyo Metropolitan University
sumikawa-yasunobu@tmu.ac.jp

Abstract: The application of historical causations to modern social issue solving is considered important inhistory education for high school. Ikejiri & Sumikawa (2016) developed a searching system to enhancehistorical analogy for by comparing historical causations related to modern social issues. Additionally, themore different historical analogies there are in a group, the more collaborative historical analogy is prompted.
However, there is no effective grouping system which groups students that make use of different historicalanalogies from each other. In this study, we propose a novel online grouping system that makes thecombination of grouping students to maximize collaborative historical analogy. First, students read a news
that a teacher prepares in advance. Second, each student selects one historical causation assigned one or morecategories from 13 categories that can be useful for solving the social issue described in the news with thesearching system. At this step, the system makes individual vectors representing what a student selected thecategories. Third, to maximize the collaborative historical analogy in each group, we use two kinds of solvers
that maximize scores for combinations of two students who have similar ideas and minimize scores for groups
that are created by the combined two students as much as possible. As a result, pairs are automatically madecomposed of two students that make use of relatively similar historical analogies from each other, and groups
are automatically made composed of two pairs that make use of relatively different historical analogies fromeach other. Finally, on the online platform, students can check the validity of their historical analogies in eachpair, consider the current social issues from two different perspectives and integrate their historical analogies
collaboratively in each group.
Keywords: History Education, Grouping, Collaborative Learning, Web Application, Analogy

INTRODUCTION
There has been a growing interest in historicalanalogy. David (2002) insists that history provides not
only information on the past but also alternativesolutions to similar modern issues. There have been afew cases wherein American politicians consider
historical lessons when they frame diplomatic policies,
which cannot be judged, based on individualexperience (Abbott & Adler, 1989). Thus, learning
history as the resource of analogy can help analyze thereasons behind existing modern social issues and thendevise alternative solutions to confront them.
Also in history education, the application ofhistorical causations in solving modern issues isconsidered important. Indeed, Japanese government’s
teaching guidelines for high school education (2009)
considers the fostering of the ability to apply historicalknowledge to modern issues to be the advanced goal.
Some researchers have developed effective learning
methods to help promoting the application of historicalcausations in solving modern problems. For example,
Mansilla (2000) examined how students successfully
apply historical causations to current issues. Ikejiri etal. (2011) designed a competitive card game for high-school students studying world history. These
researches revealed effective instructions forpromoting the transfer of historical causations
correctly: dividing information about causations into
“problem”, “solution”, and “result”, using history tobuild an informed comparative base between both pastand modern cases; recognizing contextual differences
between them; and checking the validity of historicalanalogy made by students with each other in a groupcomposed of two pairs. Moreover, Ikejiri & Sumikawa(2016) and Sumikawa & Ikejiri (2015) developed aweb application, the History Time Machine, that canhelp Japanese high school students of world history tosearch for historical causations similar to the authenticsocial issues and to transfer historical causations toauthentic social issues appearing in recent news.
However, there is no effective grouping method forpromoting collaborative historical analogy. As
Holyoak & Sagard (1980) have pointed out, what each
person thinks the similar historical event to modern one
is up to the person. For example, some American
politicians thought World War Ⅱ was similar to Gulf
War, and other thought Vietnam War was similar toGulf War. The more different historical analogies there
are in a group, the more collaborative historicalanalogy is prompted. Thus, the method is needed
which can group students that make use of different
historical analogies from each other.
Moreover, careful discussion is required using
historical analogy because historical analogy oftencauses the misuse of analogy (Fischer, 1970). Ikejiri etal. (2011) insist that a group composed of two pairs inwhich they can check the validity of each historicalanalogy is effective for the collaborative historicalanalogy. Thus, it is important to ensure that each pairis composed of two students that draw on a relatively
similar history with regard to historical analogy inorder to reduce the cognitive load in the first phase.
After that point, creating a group that is composed of
two pairs that each draw on a relatively different
history for historical analogy is important for gatheringvarious perspectives on the same social issue featured
in the news in the second phase. This method will also
create a scenario which prompts students to consider
current social issues from various perspectives.
In this study, we develop a novel grouping systemfor enhancing collaborative historical analogy. Next
section summarizes how the History Time Machinefinds similar events and what feature vector is created.

PRELIMINARIES
Algorithm of search engine
The History Time Machine detects similar events
by counting the number of same categories attached toevents. The more the same number is increased, themore similarity is also increased (Sumikawa & Ikejiri,2015). With this system, students explore daily web
news that interests them (topics that include socialissues), copy and paste the text, and select categories
related to the social issues of the news. After that, they
can search for related historical causations, identify thesimilarity between the current social issues andhistorical causations, and use the historical causations
as a resource for considering the current social issues
from a new perspective (Ikejiri & Sumikawa, 2016).

nations, and used only specific currency in order toreduce the influence of the Great Depression（=“Solution”）. As a result, it intensified the conflict
between these zones, small countries depending on
trade got poor, and international situation hasbecome more unstable.（ = “Result”）.
If historical causation is related to specificcategories, these categories are tagged “1” and others
are tagged “0”. Thus, feature vectors of all historicalcausations are created in advance, as shown in Table 1.
Table 1. The example of the vectorsof historical causations

ALGORITHM
Overview
We show how students use the History Time
Capsule for collaborative learning in Figure 1. The
shadowed boxes are newly developed processes for themain History Time Capsule.
In the research phase, students select news
categories. We regard the selected categories asperspectives which are concerns for students. We firstcombine two students with the same concerns. Then, toenhance discussions between different perspective, wecreate groups with different concerns. For this purpose,
our algorithm creates feature vectors for all students
based on the categories they select.

Feature Vector Creation
Each historical causation in The History Time
Machine is assigned one or more categories from thefollowing 13 categories; reign, diplomacy, war,production, commerce, study, religion, literature andthought, technology, popular movement, community,disparity, and environment. The description ofhistorical causation is composed of three sentences,“Problem,” “Solution” and “Result.” The following is
an example.
Title: Bloc Economy in 20th C
Category: diplomacy, commerce
Description: After the Great Depression happened
in 1929, each country tried to stabilize the economy（=“Problem”）.Then, the Great Powers made bloc
economy zone among their colonies or friendly

Figure 1. Overview of processes using “the History TimeCapsule”

Figure 2. The image of processes using “the History Time Capsule”

Algorithm for Grouping
The algorithm for grouping uses “similarity score”
that is calculated by counting the number of same “like”
categories between two feature vectors. These scores
are calculated in all combinations of the pairs formed
from all students or all combinations of groups createdfrom all pairs automatically. In creating the groups, thefeature vector of each pair is generated by adding eachnumber of the category (ex. the feature vector of thepair is {0, 2, 0, 0, 2, 0, 1, 0, 0, 0, 0, 0, 0} if one student
selects history 1 in Table 1 and the other student selects
history n in Table 1) and used for the calculation of thesimilarity score. Based on the calculated scores, thepairs are created in descending order of the similarity
score or the groups are created in ascending order ofthe similarity score.

DEVELOPMENT
According to preliminaries and algorithm describedabove, we develop a novel online grouping system,“the History Time Capsule.” We show how students
use the History Time Capsule for collaborative
learning in Figure 2. Once all students determine their
discussions with the History Time Machine, theHistory Time Capsule automatically creates groups
from the feature vectors. Then, students discuss with

their pair or group members. The details are given as
follows.

(1) Login and Selecting news
At the beginning, each student logs into the History
Time Capsule by their own accounts, and selects one
piece of interesting news. Note here that we assume
that the accounts and news are prepared by a teacher inadvance.

(2) Applying historical causations
Next, each of them searches for historicalcausations similar to the selected news with using theHistory Time Machine (Figure 3). Students selectcategories that are related to the social issues of thenews and can search for related historical causations byclicking the search button. We expect students toidentify the similarity between the current social issues
and historical causations and to use the historicalcausations as a resource for considering the current
social issues from a new perspective. From thesearching result, students predict what outcomes will
be obtained by applying historical causations to social
issues included in the news they selected.

(3) Discussion in each pair
After all students input their outcomes with theHistory Time Machine, pairs are automatically formedby this system. We expect that two students in eachpair make use of relatively similar history for historicalanalogy. Each pair collaboratively combines two
documents about their outcomes input in the History
Time Capsule (Figure 4). In the online collaborative
writing space, they can communicate each other in thechat box. We expect them to understand their historicalanalogies deeply and to check the validity of them.
After finishing their combining, each pair cansubmit the document and waits for next grouping.

Figure 3. The interface of using the History Time Machine

Figure 4. The interface of discussion in each pair in the History Time Capsule(4) Discussion in each group
After all pairs submit their documents, two pairsthat make use of different historical analogies fromeach other are automatically paired off (Figure 2). We
expect them to consider the current social issues fromtwo different perspectives; leading to check the validityof their historical analogies. They can communicate
among them in the chat box. Finally, they integrate
documents about their outcome collaboratively.
After each group submits the documents, eachdocument is automatically archived as a web page
which students can check anytime. So, we expect thatstudents reflect the predicts or idea again after a set
period of time.

CONCLUSION AND FUTURE WORKIn this study, we propose a novel online grouping
system that makes the combination of grouping
students to maximize collaborative historical analogy,
the History Time Capsule.
Future work is the verification of grouping effect oncollaborative historical analogy with the system byconducting the experiment for high-school students
who learned world history.

ACKNOWLEDGEMENTS
This work was supported by JSPS KAKENHI GrantNumbers 16K16314.

REFERENCES
Abbott, C., & Adler, S. (1989). Historical Analysis asa Planning Tool. Journal of American Planning
Association, 55(4), 467-473.
David J. Staley. (2002). A History of the Future.
History and Theory, Theme Issue, 41, 72-89.
Fisher, H. D. (1970) Historians’ Fallacies: Toward a
Logic of Historical Thought. New York: Harper& Row, Publishers.
Holyoak, K., & Thagard, P. (1980). Mental Leaps:
Analogy in Creative Thought. Massachusetts: TheMIT Press.
Mansilla, V. (2000). Historical Understanding
Beyond the Past and into the Present. In Stearns,N. P., Seixas, P. & Wineburg, S. (Eds.), Knowing
Teaching and Learning History: National andInternational Perspectives. New York: New York
University Press.
Ministry of Education, Culture, Sports, Science andTechnology – Japan. (2009). Koutou Gakkou
Gakushuu Sidouyouryou Kaisetsu. Tokyo:
Kyouiku Shuppan.
Ikejiri, R., Fujimoto, T., Tsubakimoto, Y., Yamauchi,Y. (2011). Rekishitekijisho wo Gendai no
Mondaikaiketsu ni Ouyousuru Chikara wo
ikuseisuru Kyozai no Design to Hyoka. Kyoiku
Media Kenkyu, 19(1), 1-12.

Ikejiri, R. & Sumikawa, Y. (2016). Shinsei na
Shakaisankaku wo unagasu Sekaishi no
Jugyokaihatsu: sono Hi no News to Kanrenshita
Rekishi wo Kensakudekiru system wo Mochiite.
Shakaika Kenkyu, 84, 37-48.
Sumikawa, Y., & Ikejiri, R. (2015). Mining Historical
Social Issues. Intelligent Decision Technologies(Smart Innovation, Systems and Technologies),
39,587-597.