Summary
This downloadable PDF lesson plan for English teachers helps B2 students discuss AI in hiring. This ESL class material explores the pros and cons of using technology in recruitment, covering key vocabulary and grammar for workplace discussions. This lesson engages students with a variety of activities about using AI in the workplace. It starts with a warm-up discussion and a vocabulary matching exercise. Students then complete a listening gap-fill about the promises and problems of AI in recruitment. The lesson includes grammar practice on the passive voice and conditionals, analysis of a real-world case study (Amazon), and a final role-play where students debate implementing an AI hiring tool, using newly learned phrases for discussing pros and cons.
Activities
- Students begin by discussing the ideal job candidate before learning key recruitment vocabulary like 'resume screening' and 'algorithmic bias' in a matching exercise. This sets the stage for the topic.
- A listening comprehension exercise has students fill in the gaps in a short text about the benefits and risks of AI in hiring. This is followed by discussion questions to check understanding and encourage critical thinking.
- Grammar is practiced through targeted exercises on the passive voice, for describing processes, and conditional structures, for discussing hypothetical situations related to technology and its consequences.
- The lesson culminates in a case study analysis of Amazon's biased AI tool and a dynamic role-play where students debate the adoption of a new AI system, using specific phrases for expressing pros and cons.
Vocabulary focus
This lesson introduces essential vocabulary for modern recruitment and technology. Key terms include: resume screening, Applicant Tracking System (ATS), algorithm, bias, shortlisting, soft skills, and culture fit. These words help students discuss the hiring process in a professional context.
Grammar focus
The grammar section focuses on two key areas. First, the passive voice is taught for describing automated processes where the agent is unknown or unimportant (e.g., 'applications are screened'). Second, first and second conditional structures are practiced to discuss the real and hypothetical consequences of using AI.
