SKY PROJECT REPORT NO. 3

GRASPING AND
TRAINING THE SKILLSOF GARMENT-SECTOR
WORKERS IN ETHIOPIA:
FINDINGS FROMASSESSMENTS ANDINNOVATIVE SOFTSKILLS TRAINING
EMMANUEL ESTRELLADO, NAGOYA UNIVERSITY, JAPANPIMMADA CHAROENSILP, NAGOYA UNIVERSITY, JAPANPROF. DR. SHOKO YAMADA, NAGOYA UNIVERSITY, JAPAN (SKY PROJECT LEADER)
FEKADU NIGUSSIE, ETHIOPIA (SKY ETHIOPIA NATIONAL COORDINATOR)© Skills and Knowledge for Youths ProjectGraduate School of International Development, Nagoya University
Furo-cho, Chikusa, Nagoya 464-8601, Japan
https://skills-for-development.com/

iii

Table of Contents
Executive Summary
Acknowledgment
Introduction

vii
ix
01

01.
OVERVIEW OF ETHIOPIA’S TEXTILE & GARMENT

03

CONTENTSSECTOR

iv

02.
THEORETICAL BACKBONE OF THE SKY

05

INTERVENTIONS
2.1 Competencies and their measurements

05

2.2 Challenges to soft skills development

06

03.
RESEARCH DESIGN

08

3.1 Participants08

3.2 The study framework

09

3.2.1 Quasi-experiment using the SKY Skills

09

Assessment Module
3.2.2 Game-based soft skills training

10

OVERALL RESULTS OF SKILL ASSESSMENT

1304.
4.1 Cognitive skills

13

4.2 Noncognitive skills

1405.
EFFECT OF GAME-BASED TRAINING ON

18

WORK-RELATED SOFT SKILLS
5.1 Game-based training results

19

5.2 Heterogenous analysis of work-related soft

21

skills gains

06.
CONCLUSIONS

23

07.
POLICY LESSONS AND SUGGESTIONS

24

References

26

TABLES

List of Tables

Table 1.
Background information on participants by firm size

08

Table 2.
The overall structure of the training program

11

Table 3.
Result of confirmatory factor analysis on work-related

18

soft skills

Table 4.
Actual impact of gamed based BMT on work-related

20

soft skillsvList of Figures
Figure 1.
The experimental framework

10

Figure 2.
Conceptual framework of soft skills targeted by the training program

12

Figure 3.
The developed board games used in behavioral modeling training

12

Figure 4.
Average and variance of written test results

13

Figure 5.

FIGURES

Relationship between written test by subjects

vi

14

Figure 6.
Influential factors on written test results

15

Figure 7.
Average and variance of workers' personal characteristics results

15

Figure 8.
Average and variance of work-related skills results

16

Figure 9.
Relationship between work-related skills by domains

17

Figure 10.
Changes in OHS, tidiness, efficiency, quality control, teamwork, and19

average work-related soft skills between the trained and untrainedgroupsFigure 11.
Percentage change in OHS, tidiness, efficiency, quality control,

21

teamwork, and average work-related soft skills between the trained
and untrained groups after controlling for other factors like age,gender, education, etc.

Figure 12.
Percentage gains in work-related soft skills disaggregated by gender,
position, education, training, and factory size

21

ACRONYMS

List of Acronyms

AfDB

African Development Bank

BMT

Behavioral Modeling Training

DID

Difference-in-Differences

GBT

Game-Based Training

GDP

Gross Domestic Product

ILO

International Labour Organization

IMF

International Monetary Fund

JICA

Japan International Cooperation Agency

JSPS

Japan Society for the Promotion of Science

KAKENHI

Grants-in-Aid for Scientific Research

LMTF

Learning Metrics Task ForceOECD

Organisation for Economic Co-operation and Development

OHS

Occupational Health and Safety

OJT

On-the-Job Training

PIAAC

Program for the International Assessment of Adult
Competencies

SE

Standard Error

SKY

Skills and Knowledge for Youths Project

SME

Small and Medium Enterprises

TVET

Technical and Vocational Education and Training

WRSS

Work-Related Soft Skillsvii

Executive Summary

SUMMARY

Ethiopia is a fast-growing economy, and garment production is one of the
key manufacturing sectors that drives it. Accordingly, to cultivate a higherskilled workforce in this sector, the Government of Ethiopia has expanded
Technical and Vocational Education and Training (TVET). Regardless,complaints are ceaselessly heard from employers that their employees lackthe skills they demand.

viii

SKY (Skills and Knowledge for Youths) project team of Nagoya University
Japan has been working in Africa, particularly in Ethiopia, with the aim toprovide evidence-based suggestions for effectively mitigating skills gaps
and upskilling workers. In this report, we highlight the findings from theskills assessments and effective improvement of garment-sector workers'
soft skills through our innovative training program using board games.
The paper will first introduce the overall characteristics of skills ofparticipated 501 workers in small and medium enterprises (SMEs), grasped
through our skills assessment. The assessed skills include cognitive ones
such as reading comprehension, calculation, and theoretical knowledge of
garment production, aside from practical and noncognitive or soft skills.
The necessity of soft skills is identified as always. Based on theseassessment results, the next part of the paper presents the findings fromour original soft skills training program.
Unlike conventional lecture-based training, the SKY one-day training
program is designed to help participants simulate work scenarios in acontext similar to the workplace. The psychological theory of behavioral
modeling inspired us. The program requires participants to investigate
solutions to improve work-related soft skills collectively.
The report will present strongly positive outcomes of this game-based
training in five domains of soft skills, namely, (1) occupational health andsafety, (2) tidiness and cleanliness, (3) workplace efficiency, (4) productquality control, and (5) teamwork. The effects of the game-based soft skills
training were evaluated in two ways: (1) the skills of participants were
evaluated before and after the training intervention, and (2) the skills ofparticipants were compared with those of nonparticipant groups.
In conclusion, the report discusses the implications of the outcomes fromour package of assessments and game-based training for developing
manufacturing workers' skills, particularly soft skills, in developing
countries.

ACKNOWLEDGMENT

Acknowledgment

The following financial supports enabled
the activities reported in this paper:
Grassroots Technical Cooperation
Project, the Japan International
Cooperation Agency (JICA)
Grants-in-Aid for Scientific Research(KAKENHI) Program with Grant
Number JP18KK0062, Japan Society for
the Promotion of Science (JSPS).

ix

INTRODUCTION
01

Being at the forefront of African growth,
Ethiopia has endeavored drastic reforms of
its TVET system to supply the skilledworkforce demanded in certain flagshipindustries, including garment production.

In Africa, since the turn of the millennium, the economic prospect has
been bright, driven by several of the world's fastest-growing economies,
including those of Ethiopia (8.5% annual growth in 2018; 4th in the world),
Rwanda (7.8%; 5th), Ghana (7.6%; 6th), and Côte d'Ivoire (7.0%; 9th)(International Monetary Fund [IMF], 2018). Facing such a positive
economic outlook, governments and intergovernmental organizations that
promote the sustainable growth of Africa have increased their budgets forand focus on skills development (African Development Bank [AfDB] et al.,2015; World Bank, 2018).
Being at the forefront of African growth, Ethiopia has endeavored drastic
reforms of its TVET system to supply the skilled workforce demanded incertain flagship industries, including garment production. Particularly,
TVET has seen significant expansion in sectors related to merchandise
export, which the government of Ethiopia aimed to increase from US$2
billion in 2009/10 to US$6.5 billion in 2014/15. The major sectors expected
to contribute to this growth were commercial agriculture, garments, andtextiles (Ethiopia Ministry of Finance and Economic Development, 2010).
Regardless, ceaseless complaints are heard from both the training
institutions and employers about the mismatch of expectations and limited
collaboration. School-based TVET tends to be inflexible and not costefficient, in contrast to today's fast-changing demands for skills andknowledge in the world of work. Given this situation, in recent discussions
about TVET and skills development, attention has shifted from the design
and implementation of institutionalized education programs tocompetencies acquired by learners.

To overcome the limitation of institution-based ideas of training andprovide evidence-based proposals for effective skills development, theSkills and Knowledge for Youth (SKY) project of Nagoya University waslaunched to use our academic expertise to capture the multifaceted
composition of workers' skills using its unique assessment module. Such anassessment also enabled us to compare the skills workers possess withthose demanded by employers. We measure the workers' actual andexpected skills in three dimensions: cognitive, noncognitive, and technical.
The realities of individuals' skills and employers' expectations of them arestill unclear in most industrial contexts in developing countries. Herein lies
the demands for the SKY project's constructivist approach to skills
assessment.
Another important theme of this paper is our innovative training programfor soft skills. In our experience of assessing workers' skills, without any
exceptions, we identified the unmet demands for soft skills (Yamada, 2023;
Yamada and Otchia, 2022). We were often requested to provide training to
improve such work-related soft skills, not just to identify the skills gaps. In
response to such requests, we considered our contribution on this front.
We recognized that most of the conventional soft skills training is
conducted in lecture rooms with limited opportunities for participants todigest the concepts into practice. Observing the gap in demand andavailability of effective training programs, the SKY Project developed aone-day game-based training program utilizing Bandura's theory of
behavioral modeling training.
This is done via a series of interactive board games coupled with postgame reflection sessions. The developed training program allows workers
to learn modeled behaviors, engage in hands-on activities, and practice themodeled behaviors in a simulated work environment. This game-based
training approach will ultimately bridge the gap between theory andpractice, ensuring the application of the workers' newly acquired skills intheir work environments.
In this report, we first discuss the industrial and national context. It will
also discuss some theoretical issues that justify our unique interventions.
Chapter 3 explains the participants and research design. Then, Chapter 4
will present the general picture of the 501 garment-sector workers who
took part in our assessment. It will then be followed by Chapter 5, which
introduces the SKY game-based training and its significant outcomes indeveloping participants' soft skills in a short period. The last part of thepaper will draw lessons and policy suggestions from this series ofinterventions.

02

1

OVERVIEW OF ETHIOPIA’STEXTILE & GARMENT SECTOR

Ethiopia has a long history of manufacturing textiles since the first integrated textile mill factory wasestablished in 1939 in Dire-Dawa city. In the 1960s, more integrated private textile mills were
established. Despite the nationalization of the private textile mills during the military regime from 1974
to 1991, more integrated textile mills were expanded. At present, the Ethiopian government considers
the textile and garment sector as a vital pillar for its ambitious economic industrialization strategy. Thisis evidenced by the government's rapid expansion of industrial parks to attract foreign investment in
the textile and garment industries.
The textile and garment sector has emerged as one of the most significant contributors to value-added
manufacturing production and employment. In 2021, the overall export earnings of the textile andgarment manufacturing industry were US$181.4 million, accounting for 46.5% of the total
manufacturing sector earnings and 0.6% of the total GDP (Ethiopian Monitor, 2022).
This research concentrates on the Ethiopian SME garment and textile industry because of its rapid
growth at national and global levels. In the past decade, Ethiopia has successfully transitioned its
agricultural economy into a fast-growing industrial economy through transformative industrial policies(Ethiopia National Planning Commission, 2016). The garment and textile sector receives the mostattention from the Ethiopian government due to its potential for economic and employment growth(Chang et al., 2016). Staritz et al. (2016) reported an impressive textile export share advancement from
US$9 to US$68 million within the five years from 2009 to 2014, and according to Ethiopia's Central
Statistical Agency (2018), the gross value-added distribution of the textile and garment industry wasaround 12 percent in 2017. The textile industry's expansion involves many SMEs, and these significantly
contribute to Ethiopian macroeconomic and labor demand (Buli, 2017). According to the Central
Statistical Agency (2018), the textile and garment sector engaged around 51,000 workers in 2017.

03

In parallel with its export-promotion policy, the government invests in vocational education andtraining (TVET) institutes specifically for textile-related programs (Khurana, 2018). As of 2011, fields inwhich more than half of graduates were unemployed included weaving and textile engineering,
together with woodworking, carpentry, and plumbing. At the same time, more than 50 percent ofvacancies in large and medium-sized firms are expected to be filled by skilled production workers,
compared with fewer than 10 percent by managers and professionals who hold educational certificatesin the liberal arts (Geiger and Moller, 2015). This fact points to a mismatch between labor demand andtraining, regardless of the expanded demand for and effort to train skilled workers, as well as an urgent
need for adequate policy measures to mitigate it.
One of the biggest obstacles to growth in the Ethiopian textile and garment sector is the lack of a
sufficiently skilled labor pool, not only in terms of technical skills but also soft skills (Yamada et al.,2018), which results in poor product quality and productivity (Khurana, 2018). In Ethiopia, employers
consider teamwork, efficiency, and tidiness to be crucial soft skills (Yamada, 2023). A study by Yost andShields (2017) discovered severe problems with worker motivation, ability to manage health andhygiene, and safety at the workplace. These circumstances indicate the urgent need for effective
training of work-related skills, particularly soft skills, for workers in the garment sector, a main priorityof this study.

04

2

THEORETICAL BACKBONE
OF THE SKY INTERVENTIONS

2.1. COMPETENCIES AND THEIR MEASUREMENTS
Regardless of what they are called—21st-century skills, competencies, or employable skills—ideas andpolicy measures in the recent global trend of education and development are converging toward thosethat develop learners' problem-solving skills. A practical but significant implication of this shift inpriorities is the need to develop the means for assessing such skills. Because the aim is not to examine
whether the learner has acquired established domains of knowledge, conventional tests following thecurriculum framework are not suited for this purpose (Learning Metrics Task Force [LMTF], 2014).
In the long history of standardized measurements of learning achievement, most tests have focused
exclusively on measuring the cognitive dimension of knowledge, such as calculation, reading, grasping
concepts, and memorization. However, there is a growing argument that to solve problems, having
knowledge is not enough; noncognitive abilities, such as perseverance, motivation, emotional stability,
and interpersonal communication skills, are also crucial (Anderson et al., 2001; Bowles et al., 2001;
Heckman and Rubinstein, 2001). Moreover, in the case of TVET, students should acquire functional
work-related skills (Fastré et al., 2014).
At the same time, as much as school certificates do not represent the workforce's capacities, cognitive
skills can explain only part of them. According to Bowles and colleagues (2001), cognitive skills accountfor only a minor part of the effects of educational attainment on labor market outcomes, and a largepart is yet to be explained. One reason for the lack of methods for assessing comprehensive skills,
including attitudinal ones, is that the required problem-solving skills differ across industries andcontexts. Therefore, the assessment framework should be developed endogenously, based on thespecific demands for skills of concerned industries and workplaces. Another challenge is the difficulty ofidentifying indicators to represent such skills. Recently, an increasing number of academic works on
noncognitive (soft) skills in the workplace have been published. One such study untangles the perceived
skill demands expressed in job postings, interviews, and questionnaires (Kalauz et al., 2015; Lyu and Liu,
2021). There are also case studies of workplaces observing people who work in response to skill
requirements (Grugulis and Vincent, 2009). Other than those studies that examine perceptions anddemands, some studies try to grasp the effects of the noncognitive skills of workers on salaries orpromotions. Most studies of this type conduct statistical analysis. The variables they use to represent
individuals' noncognitive skills are proxies that would suggest certain behavioral tendencies, such as acriminal record, employment in a leadership position (Kuhn and Weinberger, 2005), or length ofretention at one job (Kristof, 1996), to represent the behavioral orientation of sample populations(Heckman and Rubinstein, 2001; Kyllonen, 2013; Lindqvist and Vestman, 2011). Regardless of theirinnovative ideas to examine the demands and rewards for noncognitive (soft) skills, they rarely capturesuch skills in real work contexts. Also, most of them focus on cases of particular industries in aparticular society and do not have a comparative perspective.

05

Thanks to the creation of large international datasets, which include some measures of adult workers'
skills, an increasing number of studies have recently been published that examine the effects of skills onlabor market outcomes at the macro (national) levels (Allen and Van der Velden, 2001; Desjardins and
Rubenson, 2011; Green and McIntosh, 2007; Pellizzari and Fichen, 2017). The largest dataset of this sortis that of the Program for the International Assessment of Adult Competencies (PIAAC), conducted by
the Organisation for Economic Co-operation and Development (OECD). The PIAAC participants were
mostly developed countries, but developing countries are joining the program, and the opportunities
for analyses of the situations in these countries are also evolving (Tong et al., 2019). Still, thoseopportunities are limited, and the large datasets do not provide detailed pictures of worker–employer
relationships in response to how the skills are developed and evaluated. In summary, there remains thechallenge of assessing the varieties of worker skills in a contextualized but comparable manner.

2.2. CHALLENGES TO THE SOFT SKILLS DEVELOPMENT
Literature suggests the importance but difficulty in assessing working adults' comprehensive package ofproblem-solving skills, which the SKY project measurement can overcome. Now, let us also review
literature that discusses the training of noncognitive (soft) skills, another theme of this paper.
Soft skills training for workers has become increasingly targeted by development agencies and training
providers (Akolgo-Azupogo et al., 2021; Dar, 2016). However, literature recognizes the challenges ininventing methods and contents of training that make participants adopt behavior and mental
orientation for problem-solving.
Often, the ambiguity of the concept of soft skills makes the concrete goal setting of the training
programs to be difficult. There are two schools of thought regarding soft skills development: thegeneralist and the specifist (Kechagias et al., 2011). The generalists believe that soft skills are universal;
thus, trainees can learn general concepts of soft skills independently from any particular context (e.g.,
Ennis, 1993). In contrast, the specifists argue that trainees encounter difficulties adapting the general
concept of soft skills in problem-solving in specific contexts. The latter scholars argue that soft skills are
better taught in relation to the technical, social, and cultural contexts in which the learners use them(e.g., Dawe, 2002; Laker & Powell, 2011; Moore, 2004; Zhou, 2017). This paper joins the specifist
perspective, as our observations suggest that training participants often cannot recognize therelationship between the abstract contents of training and their daily work. Therefore, for the
program's effectiveness, it should be designed so that the participants can act on the learned soft skills
based on their own conceptions, social values, and experiences.
The selection of a training delivery mode is another challenge. Many training providers use traditionalmodes of training, such as lecture presentations, that do not involve hands-on practices (e.g., Groh etal., 2012; Ibrahim et al., 2017). Lecturing on soft skills in a generic manner without offering
opportunities for practice tends only to deposit declarative knowledge in the minds of learners.
Declarative knowledge does not stimulate the learners' consideration of 'how' to do things, which is lesslikely to be retained (Jiamu, 2012). In other words, for learners to internalize the reasons and goals forcertain behaviors, different approaches to training are desired.

06

Given the difficulty of developing behavioral soft skills, recent studies highlight the necessity of shifting
training approaches from classroom- to workplace-based methods. For instance, Talavera and PérezGonzález (2007) suggest using the actual workplace as the training site so that trainees can apply theirlessons directly to their actual work. Various methods for work simulation have been proposed,
including project-based learning, mentor-buddy systems, and role-playing for specific problems at work
(Dawe, 2002).
The SKY soft skills training is designed to contribute to overcoming the above-mentioned challenges andto meet the demands for soft skills training. Our training strategy is grounded on behavior modelingtheory (Bandura et al., 1961) that stimulates procedural understanding of the causes and goals ofproblem-solving by offering workplace-simulated rehearsal opportunities. By using board games, we
also overcome some of the challenges of work simulation if it is done in the actual workplace during
work hours.

07

3

RESEARCH DESIGN
3.1. PARTICIPANTS
The data set used in this study was collected between October and December of 2022. The training
participants surveyed in the study are employed in 21 garment firms in industrial parks on the outskirtsof Ethiopia's capital city, Addis Ababa.
We used a multistage cluster sampling design with the primary units (garment firms) selected byprobability proportional to their current number of workers at the time of sampling. The firms weredrawn from a list of garment factories operating in Addis Ababa provided by Ethiopian Enterprise
Development. Of the 389 garment apparel firms with 31,838 employees, 21 firms were randomly
selected to participate in the study. From a list of full-time employees provided by the garment
companies, 501 workers were chosen using a simple random sampling proportional to the firm's size.
The sample population was limited to full-time employees. In Ethiopia's manufacturing industry, theemployee turnover rate is high, and fluctuating orders from clients make employers to hire additional
workers temporalily. Given the longitudinal nature of this study, which compares the pre- and posttraining performances of same groups of participants, we decided to involve only full-time employees.
Table 1 shows the demographic information of the participants. Most of the them were female, at
81.8%. This reflects the dominance of female workers in Ethiopia's garment sector, where most rankand-file laborers are women, while supervisory and managerial positions are primarily dominated bymen (International Labour Organization [ILO], 2021). The average age of the participants was 25.9 years(with a standard deviation of 5.99). A third of the participants surveyed had an upper secondary
Table 1. Background information on participants by firm size.
Total

Small

Medium

Large

N=501

N=141

N=239

N=121

Gender (Male)

18%

21%

17%

17%

Age

26 (6)

25 (6)

26 (6)

26 (6)

Below Grade 11

66%

69%

64%

67%

Above Grade 11

34%

31%

36%

33%

Line worker

90%

91%

89%

88%

Manager/Supervi
sor

10%

9%

11%

12%

No

56%

70%

42%

65%

Yes

44%

30%

58%

35%

Every 8 out of 10 of participants are women.

Education
Only 3 out of every 10 participants haveupper secondary education.

Position

Every 9 out of 10 participants are line
workers.

Factory Training

Source: Data from Skills and Knowledge for Youth Program assessment

About 4 out of every 10 participantsreceived in-house training.

08

education, TVET, or tertiary education. The rest of the participants received education up to grade 10.
Managers and supervisors made up about 10.3% of the participants. Regarding receiving in-housetraining, roughly 60% of the participants reported not receiving any on-the-job training.

3.2. THE STUDY FRAMEWORKAs mentioned earlier, the objectives of this study were two-fold: one was to capture the multifaceted
composition of workers' skills using its unique assessment module, and another was to implement andevaluate the efficacy of soft skills training program using board games which the SKY project hasdeveloped based on its assessment findings and the behavioral modeling theory.
The following sections will explain the research designs and instruments used for this study. First, we will
present the design of a quasi-experiment using the SKY skills assessment to examine the efficacy of the
training program, and the introduction of the features of game-based training will follow.
3.2.1. QUASI-EXPERIMENT USING THE SKY SKILLS ASSESSMENT MODULE
With its unique research module, our study can comprehensively grasp the detailed contents of actual andself-diagnosed skills of participating workers. It allows us to examine the interrelated effects of thefollowing categories of skills on workers' productivity:
Cognitive skills: Basic knowledge, literacy, and numeracy, which can be acquired in the classroom.
Vocational skills: Operational skills for production in specific sectors.
Noncognitive ("soft") skills: Skills to apply knowledge, conduct appropriate interpersonal relations,follow the rules, and make judgments in order to achieve a required result.
Our survey is composed of three types of instruments: questionnaires, practical and written tests. For thispaper, we use the data from a questionnaire given to the workers who took part in the assessment andthe workers' test scores. The written test consists of four parts: reading comprehension, mathematics,
integrated application of knowledge, and theories of garment production.
The information provided by human resources managers helps us understand the workplace's generalcharacteristics and the demographics of the survey participants.
Data on salary, position, age, education, and self-reported noncognitive skills are taken from the workers'
questionnaires, and we use the results of the written tests to calculate variables for cognitive skills. The
variables related to the participants' self-reported attitude at work (noncognitive/soft skills) areconstructed from questionnaire items. We developed these items on noncognitive/soft skills after coding
and categorizing occupation standards of multiple countries to grasp common expectations acrosscountries, with some input from Ethiopian and Japanese specialists in garment production management.
The questionnaires capture the changes in work-related soft skills of occupational health and safety (OHS),
tidiness and cleanliness, workplace efficiency, product quality control, and teamwork. Variables for eachwork-related soft skill were constructed from 15 psychometric scale items the SKY Project teamdeveloped. Questions about participants' educational and demographic backgrounds and work
experiences were also included. Firm-level data was captured using questionnaires provided to humanresources managers of the firms that participated in the study.
We used the same standardized SKY framework for pre- and post-training assessment, which enabled us
to examine the changes in skills caused by the intervention. It was a quasi-experimental design to analyze
the impact of game-based soft skills training.

09

The participants were divided into intervention (trained) and control (untrained) groups, with the former
receiving the game-based training (Figure 1). We analyzed the data by controlling for individual and firmlevel factors such as gender, age, education, wage, position, and factory size to assess the training's
impact on participants' self-reported work-related soft skills.

Figure 1. The experimental framework
3.2.2. GAME-BASED SOFT SKILLS TRAINING
The one-day training program is designed for garment manufacturing workers, from recently hired line
operators to supervisors of production lines. In this program, we develop the capacity and motivation tocontribute to the line's collective productivity. The training also aims to allow trainees to conceptualize
soft skills and apply them to real-life workplace situations while enjoying games with colleagues.
Therefore, our training program is designed to foster workers' individual soft skills by considering theircommitment as members of the firms, leading to a more significant contribution to the line's and thefactory's shared goals.

10Table 2 shows the structure of the one-day training program. The training comprises two sessions, eachfocusing on one of the two developed board games. The whole training starts with the program
introduction, in which trainees are informed of the training's objective and have an opportunity tobrainstorm about their understanding of enhancing productivity. Each game then starts with its own
introduction and concludes with a reflection session. The introduction session briefly explains the rules,
the game's objectives, and some basic ideas involved in the game. The reflection session is essential forparticipants to internalize and conceptualize what they experienced during the game. Participants areencouraged to discuss and reflect on their behavior while considering its implications for their actual workon the production line, in order to grasp the norms and values that underlie the actions needed tosucceed in the games.
Table 2. The overall structure of the training program
Session

Time

15
mins

First
Session

10
mins
60
mins

30
mins

Activity

Training Contents

Introduction session

The objective of this session is topresent learning points to trainees tohave them grasp the purpose of the
training. The main facilitator asks
trainees to brainstorm and share how
to improve garment workers’
productivity.

Game
introduction

Garment Go
Round

Game playing

Reflection activity

This game is an intragroupcompetition. Trainees will learn theconcept of soft skills while competingwith other players.

Trainees discuss the skills learned
and discover the connection
between their reality and the skills.

60-minute lunch break
10
mins
90
mins

SecondSession

30
mins

15
mins

11

Garment Factory
Fun

Game
introduction

Game playing

This game is an intergroupcompetition. Trainees must apply soft
skills learned in the first game to be
the most productive production
team.

Reflection activity

Each team discusses and shares thestrategies that influenced theirproductivity. Trainees are guided tothink of the behaviors from the gamethat can be applied to their reality.

Wrap-up Session

This session aims to help trainees
make sense of the soft skills in theirwork situations. Trainees will discuss
skills they can bring back to theirwork environment, and share theirideas with the larger group.

SOFT SKILLS TARGETED BY THE TRAINING
In-depth consultations with local experts and observations of the working environment were conducted
to understand what problems frequently happen and determine the soft skills necessary to prevent them.
As a result, the developed training program targets skills that fall into four measurable domains of workrelated soft skills: (1) occupational health and safety (OHS), (2) tidiness and cleanliness, (3) efficiency, and(4) quality control. In addition, the training module's conceptual framework is cross-cut by (5)collaboration or teamwork skills, as depicted in Figure 2.

Figure 2. Conceptual framework of soft skills targeted by the training program

GAME DESIGN
The two board games we developed for our soft skills training are
Garment Factory Fun 1 and Garment Factory Fun 2 (Figure 3).
Garment Factory Fun 1 uses illustrated cards to model soft skills,
boosting retention. Garment Factory Fun 2 replicates factory
challenges, enabling behavior rehearsal and skills transfer.
Participants assume various roles inside the firm, collaborating tomeet orders while overcoming obstacles. Post-game discussions after
each game reinforce learning.
Our games integrate Behavioral Modeling Training (BMT) elements
proven to enhance skills transfer: rule codes, mental rehearsals,
workplace simulation, and social reinforcement. Game rules encode
learning goals. Soft skills cards promote the mental practice of soft
skills. Lastly, the game design mirrors the factory setting, and players
receive instant feedback on their progress, enhancing motivation.

Figure 3. The developedboard games used inbehavioral modeling training

Through our board game training program, we can effectively
cultivate work-related soft skills, aligning with real-world
requirements by utilizing established BMT principles. By offering
offline accessibility and context-specific training, we address
challenges African populations face, contributing to skill enhancementin the garment industry.

12

4

OVERALL RESULTS OF
SKILL ASSESSMENT
This section illustrates the overview of participants' performance, including the relationship between
different types of skills and their determinants. First, the box plot graph shown in Figures 4, 7, and 8
demonstrates average scores and variance of participants' performance on written examination, personal
characteristics, and work-related soft skills by skills domains. The graphs visualize test scores using boxes
and whisker plots. The vertical lines in the boxes show mean scores for different skill domains. Box widths
represent score distributions, and whiskers indicate the maximum and minimum scores. Dots outsidewhiskers are outliers. Narrower boxes and shorter whisker ranges suggest scores are close to the average,
while wider boxes and longer whiskers indicate more scattered scores among participants. Figure 5 shows
the relationship between the cognitive and noncognitive skills explored by our skills assessment. Finally,
we examine how background factors affect workers' cognitive scores.

4.1. COGNITIVE SKILLS
Figure 4 summarizes the written test results, categorized into four domains, namely (1) reading, (2)mathematics, (3) integrated skills (or information gathering), and (4) vocational knowledge. The resultshows that the average scores in reading and mathematics are significantly higher than those in integrated
and vocational skills. The average score of vocational knowledge is the lowest. The narrow box formathematics and vocational knowledge indicates that the score variation among the workers is small. On
the other hand, the score distribution of integrated skills is the widest. The integrated skills require theparticipants to utilize mathematics and reading literacy to gather information through graphs and tables.
Hence, the high variation and the significant gaps between integrated test scores and those ofmathematics and reading indicate that workers need higher analytical capabilities to solve complex
problems by combining multiple skills, compared to straightforward questions in reading andmathematics.

Source: Data from Skills and Knowledge for Youth Program assessment

Figure 4. Average and variance of written test results13

According to Figure 5, the domains of cognitive skills strongly correlate with each other. First, reading andcalculation skills correlate significantly with integrated skills, with .435 and .400 respectively, at the .001
probability level. However, the results indicate that workers' ability to read contributes to theunderstanding of complex tables and graphs more than the ability to calculate. Second, the contributionof integrated skills to a good theoretical understanding of vocational skills (.421 with p < .001) is morenotable than that of the reading and calculating capabilities. This finding reveals that analytical capacities
to solve complicated questions can establish advanced vocational knowledge.

Note: ***Pairwise correlation is significant at the .001 level (two-tailed).
Source: Data from Skills and Knowledge for Youth Program assessment

Figure 5. Relationship between written test by subjects
In addition to the relationship among skills, we examine the effect of background factors on the written
test score. The explanatory variables in Figure 6, include participants' demographic background,household size, education attainment, factory size, and personality traits. The coefficients for the
independent variables were determined through a regression model employing ordinary least squares,
with the dependent variable being the test scores. The blue bars represent how the listed items influence
the written test results. A longer bar, indicating a larger coefficient, signifies a more substantial effect. A
bar extending to the left represents a negative impact, while those stretching to the right indicate positiveeffects. The coefficients were shown as zero for the factors with no significant effect in the graph.
The finding indicates that workers with higher education attainment perform better in the written
examination. However, there is no difference between female and male workers. Second, the effect offactory size is negative, pointing out that workers from smaller factories tend to have higher written testscores. On the other hand, it is notable that participants' personality traits significantly influence thewritten test results. Hostile bias and emotional stability have negative effects on written test scores, while
openness and conscientiousness positively affect the results. According to this finding, workers who enjoy
learning new things and perceive others' ambiguous behaviors as nonthreatening, while following sociallyprescribed norms and rules, tend to perform excellently in the written examination. In contrast, workers

14who are better at handling negative emotions tend to have lower cognitive test scores. This phenomenon
signifies that noncognitive competencies are one of the key factors in enhancing workers' cognitive skills.

Note: Unit is the coefficient of regression analysis.
Source: Data from Skills and Knowledge for Youth Program assessment

Figure 6. Influential factors on written test results

4.2. NONCOGNITIVE SKILLSThe previous section discovers a significant relationship between workers' cognitive and noncognitive
skills. Therefore, this part will elaborate an overview of the participants' noncognitive skills assessment,
including their personal characteristics and work-related soft skills. Figure 7 demonstrates the average andvariance of workers' eight personality traits. The highest mean scores among the eight domains areconscientiousness, openness, and agreeableness. The finding indicates that the participants tend to
conform to societal standards, enjoy exploring new things, and have a cooperative orientation to others.
Another remarkable finding is that the average of hostile bias is relatively low. Despite the high variation,
this implies that the workers perceive others' behaviors as nonthreatening.

Source: Data from Skills and Knowledge for Youth Program assessment

Figure 7. Average and variance of workers' personal characteristics results15

In addition to the personality traits, the SKY assessment also captures
work-related soft skills (WRSS). The work-related soft skills consist of
five domains, namely 1) occupation health and safety, 2) tidiness, 3)
efficiency, 4) quality control, and 5) teamwork. The assessment
measures the WRSS twice, before and after the training intervention,
which will be elaborated in detail in the later section of this report.
This section illustrates only the WRSS overview of all participants
before receiving any intervention. The box plot graph in Figure 8
demonstrates the average and variation of each WRSS domain. The
score distribution has no considerable difference between the fivedomains. The average tidiness and quality control scores are thehighest, while the efficiency score is the smallest.

Source: Data from Skills and Knowledge for Youth Program assessment

Figure 8. Average and variance of work-related skills results
Additionally, Figure 9 demonstrates the pairwise correlation results
between the five domains of WRSS. The results show that every skill
domain significantly correlates with each other at the .001 level (twotailed). The most outstanding correlation is between tidiness andoccupational health and safety, with .631. This indicates that workers
who are attentive to tidiness at the workplace, tend to be highly
aware of health and safety during their duties. Likewise, the second
largest correlation size is between tidiness and quality control, with.589 (p < .001). Workers who pay attention to neat and clean
workplaces are also accurate in the observation of product quality
standards.
Given the preliminary results in the overview part, noncognitivecompetencies are markedly associated with cognitive parts ofworkers' skills. Therefore, we initiated non-conventional soft skills
training using board games, which aims to increase workers'
productivity. In the next section, this report will present the result of aquasi-experiment proving the effects of game-based soft skills training
on workers' work-related soft skills.

16Note: ***Pairwise correlation is significant at the .001 level (two-tailed).
Source: Data from Skills and Knowledge for Youth Program assessment

Figure 9. Relationship between work-related skills by domains

17

5

THE EFFECT OF GAME-BASEDTRAINING ON WORK-RELATEDSOFT SKILLSThis section will investigate how game-based training grounded on behavioral modeling theory influences
workers' work-related soft skills. Based on the theory of behavioral modeling, we will explore in thissection how game-based training will affect workers' noncognitive (work-related) skills in Ethiopia's
booming garment industry. In doing so, we will understand how soft skills are developed and provide
policy suggestions to improve the country's soft-skills training and development.
We used 15 items from the worker questionnaires to compose variables to represent the various workrelated soft skills. For each item, workers were asked to provide their opinions on the importance of aparticular workplace behavioral trait, based on a five-point Likert scale ranging from 1 = not important to 5
= very important. We then assigned each item to one of the five variables to represent the workplacerelated soft skills we wanted to analyze: 1) occupational health and safety (OHS); 2) tidiness; 3) efficiency;4) quality control; and 5) teamwork. We then used confirmatory factor analysis to verify whether theitems contributed to measuring the intended trait. The factor analysis results are summarized in Table 3.
All items exhibited positive and significant factor loadings, meaning that the items in the soft skills
assessment module can be effectively used to measure work-related soft skills and give us a better
understanding of how these skills are developed.
Table 3. Result of confirmatory factor analysis on work-related soft skills
Factor
Occupational
Health and
SafteyTidiness

Efficiency

Quality Control

Teamwork

Question Item

Coeff.

SEp

All workplaces have a first aid kit for the emergency care of an injured or ill person.

0.596

0.03330.00

Workers use protective equipment while operating machines.

0.664

0.03340.00

Workers wear clothes that are safe and easy to move.

0.658

0.03090.00

Tools are kept neatly in the toolbox.

0.791

0.038

0.00

Tools are returned to the same place after use.

0.679

0.0351

0.00

Waste is disposed into the designated trash bin.

0.519

0.03140.00

Workers do not make personal phone calls during work hours.

0.38

0.0507

0.00

The record of the material inventory is up to date.

0.701

0.04780.00

The materials are stored in the places which have the item labels.

0.586

0.0371

0.00

Workers observe the sample product first to know how the final product should
be.

0.601

0.0416

0.00

Defective products are reported to the supervisor when they are found.

0.592

0.03190.00

Workers are careful not to damage or contaminate the materials and products.

0.588

0.03070.00

Workers help each other when they need assistance.

0.498

0.02890.00

If any unusual situation occurs during work, the workers share that withcolleagues.

0.539

0.03770.00

Workers pay attention to colleagues so that any signs of trouble and dangers will
be found.

0.532

0.03990.00

Source: Data from Skills and Knowledge for Youth Program assessment

18

5.1. Game-Based Training Results
The following section presents our findings on the five domains of work-related soft skills between theintervention and comparison groups before and after the game-based training. We find that the gamebased training significantly impacts the participants' soft skills development. This section will also discuss
the factors that influence soft skill development in garment sector workers.

Legend: Trained (▃), Untrained(▃)
Source: Data from Skills and Knowledge for Youth Program assessment

Figure 10. Changes in OHS, tidiness, efficiency, quality control, teamwork, and average work-related
soft skills between the trained and untrained groups
Figure 10 shows the changes in each work-related soft skill before and after the implementation of game-based
training for both trained and untrained workers. Before the training, the values of the various work-related soft skills
and their average were comparable between the two groups. We can see that work-related soft skills for the trainedgroup increased significantly after the training. In contrast, the work-related soft skills of the comparison groupremained relatively the same. The results indicate that the game-based training intervention had a statisticallysignificant effect on all five domains of work-related soft skills. The participants in the intervention groupdemonstrated percentage point gains ranging from 6.42 to 12.1 percent compared to the untrained group.
A difference-in-differences (DID) regression approach was used to measure the actual training effects on the
population that underwent the game-based training. The DID approach is employed primarily in quasi-experimental
design studies that use panel data obtained from a baseline and treatment group to obtain a counterfactual toestimate the treatment's effect
Table 4 presents our findings on the impact of game-based training on participants' work-related soft skills after
controlling for other factors such as age, gender, education, wage, position, factory size, and on-the-job training(OJT). In all five domains of work-related soft skills and overall average, the Game-based training (GBT) impact showsthat the intervention had a significant effect on participants, with percentage point gains across all self-reported
work-related soft skills scores ranging from 6.69 to 11.7 (Table 3, models 1 to 5). Model (6) shows that, on average,
the intervention effect is at 8.34 percentage points (8.34 / 27.2 = 30.6% change). All GBT Impact estimators are
positive and significant, at least at the 1% level. Also, the effect size of our training program was significantly higher
than those reported by earlier studies. For comparison, we computed the game-based training effect size to be 0.52,
whereas past BMT trainings only have an effect size of 0.25. A twofold increase!

19

Table 4. Actual impact of gamed-based BMT on work-related soft skills
Soft skill (1)Soft skill (2)Soft skill (3)Soft skill (4)Soft skill (5)OHS

Tidiness

Efficiency

Qualitycontrol

Teamwork

0.357

0.357

1.783

-0.681-0.9080.182(-1.658)(-1.455)(-1.744)(-1.552)(-1.786)(-1.21)-0.437

0.637

1.243

1.249

0.387

0.616

(-0.806)(-0.689)(-0.844)(-0.728)(-0.839)(-0.534)

11.699***7.772***

6.687**

8.195***

7.329**

8.336***(-2.359)(-2.043)(-2.414)(-2.001)(-2.351)(-1.633)

0.873

0.228

-2.195-0.35-0.607-0.41(-1.123)(-1.091)(-1.342)(-0.855)(-1.202)(-0.856)-0.057-0.035

0.061

0.024

-0.001-0.002(-0.083)(-0.06)(-0.078)(-0.059)(-0.066)(-0.051)-0.016-0.594

0.178

0.245

-0.45

-0.127(-0.903)(-0.841)(-0.925)(-0.762)(-0.928)(-0.681)-1.0820.006-0.025-0.191-1.247-0.508(-1.104)(-1.303)(-1.216)(-0.89)(-0.866)(-0.944)

1.4

0.972

3.268*

0.916

2.303*

1.772*(-1.091)(-0.975)(-1.482)(-1.039)(-1)(-0.819)-0.226-0.253-0.3760.23

1.673**

0.209(-0.652)(-0.58)(-0.619)(-0.544)(-0.59)(-0.468)

1.037

0.025

1.918*

0.542-0.5360.597(-0.907)(-0.778)(-0.893)(-0.752)(-0.872)(-0.645)

29.498**27.709**19.566*28.036***32.806***27.523***(-8.979)(-10.27)(-9.765)(-7.123)(-7.008)(-7.545)

0.509

0.499

0.422

0.47

0.425

0.534

Post
GBT
GBT Impact
GenderAge
Education
Wage
Position
Factory size
OJT
Constant
R-squared

Average of
all workrelated soft
skills (6)Source: Data from Skills and Knowledge for Youth Program assessment
Notes: Cluster-robust standard errors are in parentheses.
All models include pre-training covariates of work-related soft skills: OHS pre, tidiness pre, efficiency pre, quality control
pre, and teamwork pre.
* p < .05; ** p < .01; *** p < .001

One of the domains of work-related soft skills for which the game-based training had the biggest effects were OHS(11.7 / 28.7 = 40.8% change) and quality control (8.20 / 27.9 = 29.4% change). These results indicate that before thistraining, participants had not been exposed to the concept of taking personal responsibility for their health,workplace safety, and quality control. After participants were provided with behavior models and game-based
rehearsal opportunities to consider these workplace issues, they retained their training.
The soft skills of tidiness and efficiency also benefitted significantly from this training. Keeping workstations tidy andclean and performing assigned tasks efficiently are frequently mentioned by employers as fundamental soft skills for
newly employed workers. The study results suggest that mutual enforcement of supervisors' daily advice andorganized training interventions like ours would enhance the development of these soft skills among workers. The
fact that the variable OJT (2.034, p = .027) has a significant effect on the improvement of efficiency skills supports
the interpretation that some support already exists within workplaces to improve these soft skills, albeit
insufficiently, and that OJT enhances the efficacy of BMT.
In some domains of soft skills, being in a managerial position affects the impact of BMT. Regarding efficiency andteamwork, managers outperformed others (3.43 at p = .028 and 2.169 at p = .044, respectively). This trend is also
found in the overall average score of work-related soft skills (1.83 at p = .036).

20

Figure 11 summarizes the percentage point changes in each domain of measurable work-related soft skills.
Percentage Gain

40.8%

OHS
Tidiness
Efficiency
Quality Control
Teamwork
Ave. WRSS
0.00

28.5%
35.3%
29.4%
22.2%
30.6%

10.00

20.00

30.00

40.00

50.00

Source: Data from Skills and Knowledge for Youth Program assessment

Figure 11. Percentage change in OHS, tidiness, efficiency, quality
control, teamwork, and average work-related soft skills between the
trained and untrained groups after controlling for other factors likeage, gender, education, etc.

5.2. Heterogenous Analysis of Work-Related Soft Skills Gains
Figure 12 shows the percentage point gains in work-related soft skills disaggregated by gender, position, education,
training, and factory size. We see that non-manager female workers without higher education from medium andlarge firms would benefit the most from our BMT game-based training program.

Note: Insignificant GBT Impact is denoted as zero.

Figure 12. Percentage gains in work-related soft skills disaggregated by gender, position, education,
training, and factory size
21

Disaggregating the game-based training effects by gender shows that female workers gained more from the training
than their male counterparts. All WRSS significantly increased for female workers, whereas males only improved interms of OHS, tidiness, and quality control. When analyzing the training impact by the trainees' position in the firm,
only non-managers or line workers had significant gains in their WRSS. Training effects by participants' level of
education show that those without upper secondary education benefit the most from the game-based behavioral
modeling training. The finding suggests that these subgroups do not possess the relevant work-related soft skills
demanded by Ethiopia's garment and textile industry. Considering that the pool of human resources employed in thegarment industry are women (82%), non-managers (90%), and with education below upper secondary (66%),
Ethiopia's garment sector lacks a skilled workforce that is demanded by the industry.
Looking at whether or not participants received in-house training or not, participants who received OJT gained themost from the training, especially in the domains of efficiency and teamwork. The findings highlight that existing
training provided by the firms is insufficient.
Analyzing the impact of the training by firm size reveals that medium and large firms stand to gain the most from thetraining intervention. The findings highlight that medium and large firms have a workforce that lacks the necessary
work-related soft skills.
Overall, the study provides empirical evidence that game-based training grounded in behavioral modeling theory caneffectively enhance work-related soft skills among garment sector workers. The results highlight the importance ofincorporating contextualized training interventions and providing opportunities for rehearsal and skill transfer in theworkplace.
These findings have significant implications for policy and practice in the garment sector and beyond. By recognizing
the value of game-based training and its impact on soft skill development, policymakers and training providers candesign and implement effective training programs that address the specific needs of workers in various industries.
The study underscores the potential of game-based training approaches in developing countries, where access tocomputers and the Internet may be limited.

22

6

CONCLUSIONCONCLUSION

23

The findings, based on a quasi-experimental DID approach,demonstrate that the game-based BMT training program has astatistically significant effect on improving Ethiopian garment
workers' work-related soft skills. The computed effect size forour training is also larger than the effect size of previous forms
of BMT training. Therefore, this study contributed statisticalevidence of the efficacy of contextualized soft skills training.
Work-related skills training conducted in the workplace requires
employers to commit time, space, and human resources neededfor operations. However, we have demonstrated that by using
board games to represent simplified workplace realities andcombining them with a BMT approach, our one-day training
program can minimize the resources required to effectively train
soft skills and incorporate work-simulated rehearsal
opportunities for better motivation, retention, and skills
transfer.
In addition to the main results of our study, we identified
subgroups that benefit the most from the game-based training
intervention. The study identified that non-manager female
workers without higher education from medium and large firms
benefit the most from our game-based training program.
We want to emphasize that the BMT approach using physicalgames is well-suited to developing countries like Ethiopia. BMT
training has been proven by scholars to be effective, but moststudies have used web- or computer-based games, which can be
expensive to implement and potentially exclude theparticipation of underprivileged populations. Access to acomputer or the internet remains relatively rare in many
developing countries like Ethiopia. Given these conditions, ourgame–based BMT using physical boardgames has great potential
to support young industrial workers in Ethiopia and many otherdeveloping countries.
This study provides a new perspective on how soft skills training
can be conducted using a game-based training approach aside
from the traditional rote-based lecture trainings provided. Our
study also bridges the missing link between the ongoing
discussion on the importance of soft skills and the lack ofeffective training methods.

7

POLICY LESSONSAND SUGGESTIONS

Based on the results, we suggest policymakers and industry stakeholders canconsider the following policy actions to promote the development of workrelated soft skills, for production line workers in manufacturing sectors indeveloping economies:

01

More participatory training in the environment
closer to the actual workplace is important for
improving soft skills.
Prioritize more participatory training situated in environments closely
resembling the actual workplace to enhance soft skills. Even when
workers received in-house training, those who underwent training still
exhibited gains comparable to their untrained peers. This underscores thelimitations of traditional training methods, such as lecture-stylepresentations, which lack hands-on learning components. The following
are suggestions to improve Ethiopia's current soft skills training program:
1. Incorporate game-based training grounded in behavioral modelingtheory into existing soft skills training initiatives.
2. Encourage collaboration between training providers, industry
associations, and garment firms to integrate game-based behavioral
modeling training into existing on-the-job training to enhance
workers' soft skills development further.
3. Allocate resources for developing and distributing board games thatsimulate workplace environments for soft skills development.

24

02

Target the training for women, less skilled andinexperienced population in SMEs.
The study has shown population subgroups that had significant gains
when using a game-based behavioral training approach. The following aresuggestions for different population subgroups to develop a more
motivated and skilled workforce:
1. Women. Developing targeted game-based training programs for
women in the garment sector will address the gender disparity inwork-related soft skills.
2. Non-managers. Training programs tailored explicitly for nonmanagerial workers with low educational attainment will provide
them with the necessary soft skills for professional growth anddevelopment.
3. Workers from medium and large firms. Game-based training iseffective, particularly in medium and large firms. Focusing on thissubgroup will ensure the development of the necessary soft skills
across the industry.

03

Collaboration and sharing are the keys to soft
skills improvement.
The game-based behavioral model training effectively develops the workrelated soft skills of garment sector workers. This training method can also
be used in different industrial contexts. We suggest the following
measures in order to achieve this:
1. Create a platform for sharing best practices in game-based training
approaches and their application in different industrial contexts.
2. Establish industry-wide forums or networks to encourage knowledge
exchange among garment firms, trainers, and policymakers.
3. Establish partnerships between training institutions, providers,industry associations, and garment firms to ensure alignment
between training curricula and industry requirements.

By implementing these policy recommendations, stakeholders can enhance
the work-related soft skills of garment sector workers in Ethiopia, improvetheir employability, and contribute to the overall growth and productivity notjust of the garment industry but also of other industries as well.
25

REFERENCES
African Development Bank (AfDB), Organisation for Economic Co-operation and Development OECD, United Nations Development
Programme (UNDP), 2015. African Economic Outlook 2015. OECD. https://doi.org/10.1787/aeo-2015-en
Akolgo-Azupogo, H., Rubens, A., Bardy, R., 2021. Soft skills in developing economies: An African view on the hidden linkage
between indigenous knowledge and business perspectives. Journal of African Studies and Development 13, 47–58.
https://doi.org/10.5897/JASD2021.0625
Allen, J., Van der Velden, R., 2001. Educational Mismatches versus Skill Mismatches: Effects on Wages, Job Satisfaction, and Onthe-Job Search. Oxf Econ Pap 53, 434–452.
Anderson, L.W., Krathwohl, D.R., Airasian, P.W., Cruikshank, K.A., Mayer, R.E., Pintrich, P.R., Raths, J., Wittrock, M.C. (Eds.), 2001.
A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives. Longman, NewYork.
Bandura, A., Ross, D., Ross, S.A., 1961. Transmission of aggression through imitation of aggressive models. The Journal of
Abnormal and Social Psychology 63, 575–582. https://doi.org/10.1037/h0045925
Bowles, S., Gintis, H., Osborne, M., 2001. Incentive-Enhancing Preferences: Personality, Behavior, and Earnings. American
Economic Review 91, 155–158. https://doi.org/10.1257/aer.91.2.155
Buli, B.M., 2017. Entrepreneurial orientation, market orientation and performance of SMEs in the manufacturing industry:
Evidence from Ethiopia enterprises. Management Research Review 40, 292–309. https://doi.org/10.1108/MRR-07-2016-0173
Chang, H.J., Hauge, J., Irfan, M., 2016. Transformative industrial policy for Africa. Addis Ababa.
Dar, A., 2016. Skills development in a global context: towards a future ready workforce [WWW Document]. World Bank. URL
https://www.worldbank.org/en/news/speech/2016/08/15/skills-development-in-a-global-context-towards-a-future-readyworkforce (accessed 1.30.23).
Dawe, S., 2002. Focussing on generic skills in training packages. National Centre for Vocational Education Research (NCVER),
Australia, Kensington Park.
Desjardins, R., Rubenson, K., 2011. An analysis of skill mismatch using direct measures of skills (No. 63). Paris.
https://doi.org/https://doi.org/10.1787/5kg3nh9h52g5-en
Ennis, R.H., 1993. Critical thinking assessment. Theory Pract 32, 179–186. https://doi.org/10.1080/00405849309543594
Ethiopia Central Statistical Agency, 2018. Report on Large and Medium Scale Manufacturing and Electricity Industries Survey.
Addis Ababa.
Ethiopia Ministry of Finance and Economic Development, 2010. Growth and transformation plan 2010/11-2014/15. Volume I:
Main text. Volume II: Policy matrix. Addis Ababa.
Ethiopia National Planning Commission, 2016. Growth and Transformation Plan II (GTP II). Addis Ababa.
Fastré, G.M.J., van der Klink, M.R., Amsing-Smit, P., van Merriënboer, J.J.G., 2014. Assessment criteria for competency-based
education: a study in nursing education. Instr Sci 42, 971–994. https://doi.org/10.1007/s11251-014-9326-5
Geiger, M.T., Moller, L.C., 2015. Fourth Ethiopia economic update : overcoming constraints in the manufacturing sector (English).
Washington, D.C. .
Ethiopian Monitor, 2022. Govt Targets $250m Annual Revenue from Textile & Apparel Exports [WWW Document]. Ethiopian
Monitor. URL https://ethiopianmonitor.com/2022/09/16/govt-targets-250m-annual-revenue-from-textile-apparel-exports/(accessed 8.4.23).

26

Green, F., McIntosh, S., 2007. Is there a genuine under-utilization of skills amongst the over-qualified? Appl Econ 39, 427–439.
https://doi.org/10.1080/00036840500427700
Groh, M., Krishnan, N., McKenzie, D., Vishwanath, T., 2012. Soft skills or hard cash? The impact of training and wage subsidy
programs on female youth employment in Jordan, Policy Research Working Papers. The World Bank.
https://doi.org/10.1596/1813-9450-6141
Grugulis, I., Vincent, S., 2009. Whose skill is it anyway?: ‘soft’ skills and polarization. Work, Employment and Society 23, 597–615.
https://doi.org/10.1177/0950017009344862
Heckman, J.J., Rubinstein, Y., 2001. The Importance of Noncognitive Skills: Lessons from the GED Testing Program. American
Economic Review 91, 145–149. https://doi.org/10.1257/aer.91.2.145
Ibrahim, R., Boerhannoeddin, A., Bakare, K.K., 2017. The effect of soft skills and training methodology on employee performance.
European Journal of Training and Development 41, 388–406. https://doi.org/10.1108/EJTD-08-2016-0066
International Labour Organization (ILO), 2021. More women in leadership for a sustainable garment and textile industry in
Ethiopia [WWW Document]. URL https://www.ilo.org/africa/technical-cooperation/inclusiveindustrialization/WCMS_823313/lang--en/index.htm (accessed 1.21.23).
International Monetary Fund (IMF), 2018. World Economic Outlook (October 2018) [WWW Document]. International Monetary
Fund. URL https://www.imf.org/external/datamapper/datasets/WEO (accessed 10.30.18).
Jiamu, C., 2012. The great importance of the distinction between declarative and procedural knowledge. Análise Psicológica 19,
559–566. https://doi.org/10.14417/ap.387
Kalauz, M.S., Hudec, G., Kirinic, V., 2015. Soft skills perception among students: importance and performance, in: Central
European Conference on Information and Intelligent Systems. Faculty of Organization and Informatics Varazdin, Varazdin, pp.
89–95.
Kechagias, M., Welsh, K.U., Stewart, M., Mearns Konstantinos Kechagias, A.G., Papadopoulou, D., Agapidou, E., Kalivas, I.,
Ananiadis Peter Wåglund, P.S., Marianne Jonsson, E., Norling, L., Rask, T.R., Stephanie Plompen, N., Snippert, D., Terpstra, P.,
Hupkes, P., Botke, J., 2011. Teaching and Assessing Soft Skills. 1st Second Chance School of Thessaloniki, Thessaloniki.
Khurana, K., 2018. An overview of textile and apparel business advances in Ethiopia. Research Journal of Textile and Apparel 22,
212–223. https://doi.org/10.1108/RJTA-01-2018-0003
Kristof, A.L., 1996. Person–organization fit: An integrative review of its conceptualizations, measurement, and implications. Pers
Psychol 49, 1–49. https://doi.org/10.1111/j.1744-6570.1996.tb01790.x
Kuhn, P., Weinberger, C., 2005. Leadership Skills and Wages. J Labor Econ 23, 395–436. https://doi.org/10.1086/430282
Kyllonen, P.C., 2013. Soft Skills for the Workplace. Change: The Magazine of Higher Learning 45, 16–23.
https://doi.org/10.1080/00091383.2013.841516
Laker, D.R., Powell, J.L., 2011. The differences between hard and soft skills and their relative impact on training transfer. Hum
Resour Dev Q 22, 111–122. https://doi.org/10.1002/hrdq.20063
Learning Metrics Task Force (LMTF), 2014. Brussels meeting summary report hosted by UNESCO. Brussels, Belgium.
Lindqvist, E., Vestman, R., 2011. The Labor Market Returns to Cognitive and Noncognitive Ability: Evidence from the Swedish
Enlistment. Am Econ J Appl Econ 3, 101–128. https://doi.org/10.1257/app.3.1.101
Lyu, W., Liu, J., 2021. Soft skills, hard skills: What matters most? Evidence from job postings. Appl Energy 300, 117307.
https://doi.org/10.1016/j.apenergy.2021.117307
Moore, T., 2004. The critical thinking debate: How general are general thinking skills? Higher Education Research andDevelopment Society of Australasia 23, 3–18. https://doi.org/10.1080/0729436032000168469
Pellizzari, M., Fichen, A., 2017. A new measure of skill mismatch: theory and evidence from PIAAC. IZA J Labor Econ 6, 1.
https://doi.org/10.1186/s40172-016-0051-y
Staritz, C., Plank, L., Morris, M., 2016. Global Value Chains, Industrial Policy, and Sustainable Development - Ethiopia’s Apparel
Export Sector. Geneva, Switzerland.

27

Talavera, E.R., Pérez-González, J.C., 2007. Training in socio-emotional skills through on-site training. European Journal of
Vocational Training 40, 83–102.
Tong, T., Li, H., Greiff, S., 2019. Human capital and leadership: The impact of cognitive and noncognitive abilities. Appl Econ 51,
5741–5752. https://doi.org/10.1080/00036846.2019.1619022
World Bank, 2018. The World Development Report 2018: Learning to Realize Education’s Promise. Washington, DC.
Yamada, S., 2023. Constructivist analysis of cross-sectional data on varieties of skills: Contextualities and generalities of skills
packages and rewards to them in Ghana and Ethiopia. Int J Educ Dev 102, 102851.
https://doi.org/10.1016/j.ijedudev.2023.102851
Yamada, S., Otchia, C.S., 2022. Differential effects of schooling and cognitive and non‐cognitive skills on labour market outcomes:
The case of the garment industry in Ethiopia. Int J Train Dev 26, 145–162. https://doi.org/10.1111/ijtd.12252
Yamada, S., Otchia, C.S., Shimazu, Y., Taniguchi, K., Nigussie, F., 2018. Bridging the Supply-Demand Gaps of the Industrial
Workforce: Findings from a Skills Assessment of Garment Workers in Ethiopia . Nagoya, Japan.
Yost, M., Shields, L., 2017. Ethiopia’s Emerging Apparel Industry: Options for Better Business and Women’s Empowerment in a
Frontier Market. Paris.
Zhou, K., 2017. Non-cognitive skills: Potential candidates for global measurement. Eur J Educ 52, 487–497.
https://doi.org/10.1111/ejed.12241

28

Project for Industrial Skills Development
and Skills Assessment in Africa
Project Leader:Prof. Dr. Shoko Yamada, Nagoya University, Japan
Members:
Dr. Christian Otchia, Nagoya University, Japan
Dr. Yuki Shimazu, Aichi Shukutoku University, Japan
Dr. Kyoko Taniguchi, Hiroshima University, Japan
Dr. Natsuki Kondo, Nagoya University, Japan
Yujiro Yamazaki, Nagoya University, JapanMark Kenneth Camiling, Nagoya University, Japan
Emmanuel Estrellado, Nagoya University, Japan
Pimmada Charoensilp, Nagoya University, Japan
Francia Randriatiana, Nagoya University, Japan
Dr. Aya Mizutani
Fekadu Nigussie, Ethiopia (Ethiopia National Coordinator)
Philip Aniah, Ghana (Ghana National Coordinator)
Nomvuyo Molefe, South Africa (South Africa National Coordinator)

CONTACT
Skills and Knowledge for Youths
skills-for-development.com
Nagoya University, Furo-cho
sky.project.adm@gmail.com
Chikusa-ku, Nagoya,Japan 464-8601