Skip to content
#generative ai Open access

Five-Day Marketing and Sales Programme for Refugee Women: Outcomes, Evidence and Recommendations for Future Cohorts (ARWO Cohort 1 Evaluation Report)

Oct 2026 · Zenodo (CERN European Organization for Nuclear Research)
Migration, Ethnicity, and Economy

Abstract

This report evaluates the first cohort of a five-day marketing and sales training programme delivered to fifteen refugee women in Kuala Lumpur, Malaysia, in September 2026 by the Afghanistan Refugee Women's Organisation (ARWO). The programme was designed to convert existing production skills — soap-making, candle-making, baking, tailoring and hairdressing — into income by teaching pricing, customer identification, sales communication, mobile-first digital marketing, generative AI tools, packaging and labelling, culminating in a supervised market-testing day with real customers. The evaluation applies Kirkpatrick's four-level training evaluation model (Reaction, Learning, Behaviour, Results) to a structured bilingual Dari–English post-course survey completed by all fifteen participants (100% response rate). Two composite indices are reported: a Programme Quality Index (95.2/100) and a Skill Confidence Index (83.1/100, Cronbach's α = 0.92), alongside pre-set key performance indicators. Headline results: 80% of participants completed a sale or confirmed booking on market day against a target of 70%; seven of the eight participants who had never sold anything previously made their first-ever sale; 87% reported increased confidence in selling; and 100% used generative AI for at least one marketing task. Two digital-adoption targets were not met, for a documented structural reason — most participants hold a single mobile number shared with family communication, which cannot simultaneously run a personal and a business WhatsApp account. The report documents two further findings of wider relevance. First, refugee-related mobility and safety constraints required the selection of safer but lower-footfall market-testing venues, and the evidence indicates that sales volume reflected constrained market access at least as much as participants' selling ability. Second, 20% of respondents read the right-to-left rating grid in reverse, a measurement artefact with implications for survey design in right-to-left languages. The report includes the full curriculum, a competency rubric, the evaluation instrument, item-level statistics and nine evidence-linked recommendations. It is intended as a transferable model for livelihood and economic-empowerment programming with displaced populations.

View source

Similar papers

#artificial intelligence Conference Open access Apr 2020

ECCOLA - a Method for Implementing Ethically Aligned AI Systems

The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.

Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson · 64 citations · ⚡6
#computer vision Review Apr 2024

AI-powered Code Review with LLMs: Early Results

The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.

Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al. · 62 citations · ⚡3
#computer vision Open access Mar 2024

LLM-based agents for automating the enhancement of user story quality: An early report

The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.

Zheying Zhang, M. Rayhan, Tomas Herda et al. · 48 citations · ⚡4
#computer vision Review Mar 2024

System for systematic literature review using multiple AI agents: Concept and an empirical evaluation

This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.

Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al. · 44 citations · ⚡2
#computer vision Feb 2024

Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysis

The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.

Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al. · 41 citations

Related blog posts

MIT News · Artificial Intelligence Oct 15, 2026

AI model decodes the language cells use to communicate

A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.

GPT-Lab Oct 14, 2026

Building trustworthy AI: The role of AI harnesses, intent contracts and evals

AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post Building trustworthy AI: The role of AI harnesses, intent contracts and evals appeared first on GPT-Lab.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.