A Personal Reflection: Redefining Translation Curricula & Pedagogy through Competency-Based Education in the Post-AI Era !

Following my recent panel participation at Sultan Qaboos University for International Translation Day alongside esteemed colleagues, I’ve been reflecting on a central challenge facing higher education: How do we design translation programs that deliver genuine professional competence in an age dominated by generative AI and automation? 

Debates in translator training often used corporate learning frameworks (such as the 70-20-10 model) against traditional academic pedagogy. While workplace learning is indispensable, university education must never be reduced to a passive "10% theory" baseline. Academia is precisely where critical thinking, linguistic authority, critical AI literacy, and ethical judgement are cultivated. 

To bridge the divide between classroom instruction and modern Language Operations (LangOps) reality, I advocate for a developmental, competency-based framework tailored to each degree level:

 1. Undergraduate Programs: From Pedagogy to Semi-Professional Practice In the foundational years, pedagogical translation builds essential linguistic and analytical skills. However, as students reach Year 4, the curriculum must transition deliberately toward semi-professional training:

 • Simulated Work Environments: Integrating on-campus translation bureau workflows, CAT tools, machine translation post-editing (MTPE), and applied AI literacy brings students to a functional/ operational / acceptable competence.

 • Flexible Market Exposure: Where institutional resources, workloads, and student-teacher ratios permit, this transition can be operationalised through structured external internships or innovative, campus-embedded work practices before graduation. 

2. Postgraduate (MA) & Micro-Credentials: Andragogy and University) MA Cohorts Feature Hybrid Student Profiles—Bringing Together Ongoing Practitioners, Career Switchers, and Traditional Graduates. Lecture-heavy instruction fails in this environment. 

 • Andragogical & Self-Directed Learning: MA instruction should shift toward andragogical approaches...leveraging the rich experience within the room through peer-to-peer interventions, collaborative problem-solving, and co-created knowledge. 

• Applied, Project-Based Pathways: This self-directed approach thrives in applied, project-based MA programs and micro-credentials rather than purely theoretical tracks. Structuring postgraduate work around client projects, portfolio development, and advanced critical AI literacy audits fosters operational autonomy and strategic leadership. 

 3. Entrepreneurial Literacy & Language Operations (LangOps) Technical proficiency alone is no longer sufficient. Translators must graduate with freelancing and entrepreneurial acumen: 

• Incorporating business fundamentals, negotiation, client communications, and gig-economy dynamics alongside AI-assisted workflow management provides graduates with true career agency and financial independence.

 4. Reinterpreting "Friction" Through Critical AI Literacy The concept of "friction"—that deliberate cognitive pause to question, critique, and refine—is crucial. However, friction should not be used as an excuse to delay teaching technology. Instead, friction is the core mechanism of critical AI literacy. By embedding AI directly within learning scenarios, we train students to interrogate where, why, and how generative models fail—transforming friction into high-level editorial judgement that empowers students to audit and direct technology confidently as language architects. 

To sum up… Academia and industry need not exist at odds. By aligning undergraduate curricula toward societal/semi-professional roles/readiness and transforming postgraduate degrees into self-directed, project-driven spaces rooted in critical AI literacy, we can build robust competency-based programs that uphold academic depth while empowering graduates for the post-AI landscape.

Last, but not least, thanks a million tothe organisers of the event, especially Dr Abdul Gabbar and HoD of the Department of English and Translation, Dr Faisal Al-Saidi, for their very welcome invitation.

Beyond the Silo: Why the Future of Translation Is a Pedagogical Challenge

For a long time I felt I was balancing two professional identities. I was a scholar of translation studies, immersed in the nuances of cross-lingual communication; and my doctoral work was rooted firmly in education, in how we structure learning, design curricula and foster critical thinking in professional contexts such as translation. I used to think I had to keep these worlds apart. I was wrong.

In the age of AI, the biggest hurdle for our industry is not technology adoption. It is pedagogy.

The Educational Crisis in Translation

When we talk about the 'talent drain' in translation, we are not just talking about software. We are talking about an educational crisis. We have been teaching translation as a manual, linear skill. To thrive in the AI era, students need to become researchers, auditors and meta-cognitive architects of their own workflows.

This is where my background in education has become my most valuable tool. Doctoral training did not just teach me to manage a classroom; it taught me to dismantle old concepts and build new, effective mental models.

The Hybrid Identity

As a translation pedagogy practitioner and specialist, I have realised that the 'language intelligence architect' we need today is fundamentally an educated learner. To be a great translator today, you must be a great student of your own process. That is why I am pivoting my professional identity toward translation pedagogy design.

• It is not just a translation course. It is an educational experience that uses the Augmented Iterative approach to teach students how to think through problems with an LLM.
• It is not just proofreading. It is a pedagogical assessment design, the Audit Trail, that requires students to justify their cognitive choices against the AI's suggestions.
• It is not just theory. It uses the deep epistemological foundations of translation studies as a diagnostic tool to critique machine output.

If we do not bring our deep knowledge of pedagogy into our translation studies classrooms, we will keep producing graduates who are technically proficient but critically empty.

Are you seeing this merge in your own work? Has your training in one field, such as education, unexpectedly become the 'killer app' for your success in translation?

Stop Training Translators for a World That No Longer Exists

A dangerous misconception persists in higher education: that translation and multilingual communication are linear, bilingual text-transfer tasks, a mechanical exchange in which a source text goes in and a target text comes out. That outdated assumption leaves legacy academic programmes fundamentally misaligned with reality, now that large language models (LLMs) handle basic linguistic transfer with ease.

From Transfer to Workflow

To remain viable, universities in Canada and the GCC alike must dismantle this legacy framework and rebuild their programmes across their theoretical, conceptual, practical and professional dimensions. We must move from the traditional transfer paradigm to a dynamic workflow paradigm (Andani, 2025). That means shifting our theoretical foundations away from simple bilingual equivalence and towards a process-oriented cognitive partnership (Simbolon, 2024), in which the human is elevated to strategic architect of complex, technology-driven language ecosystems.

What Is at Stake

On a practical and professional level, treating translation as a mere text-matching exercise does a profound disservice to students, regional economies and vital social institutions. In Canada, robust human stewardship is a legal and democratic safeguard, protecting systemic integrity in public health, law and multicultural inclusion against the risks of unchecked algorithmic output.

Across the GCC, language services are a strategic national asset driving economic diversification and Vision 2030 initiatives, in Saudi Arabia and elsewhere. Safeguarding cultural dignity, regional nuance and "face" in Arabic demands sophisticated human intervention that generic, Western-centric AI simply cannot replicate.

Takeaway

Our pedagogy, or andragogy if you prefer, must pivot away from rote error correction and towards training highly specialised linguistic engineers equipped with advanced AI literacy, prompt engineering and risk-based auditing skills to drive the global knowledge economy. Legacy courses, translation studies and specialised translation courses included, need thorough epistemological revision and redesign. We are dealing with different concepts and constructs. We need to upskill our competencies and upgrade our conceptual framework in translation.

AI Has Changed Assessment; Higher Education Has Not Caught Up

AI has already transformed how learners think, solve problems and produce knowledge. Higher education assessment, meanwhile, remains largely unchanged. A clear gap is opening between how students actually work and how they are evaluated.

Students use AI to accelerate learning, iterate rapidly and reach knowledge beyond the formal curriculum. In many cases they are becoming more adaptive and efficient than the systems designed to assess them. Yet they stay discreet about it, largely because current models still penalise or misread AI-assisted work.

A fundamental misalignment

We claim to value critical thinking and real-world readiness, yet we continue to assess controlled, decontextualised outputs.

Frameworks such as learning analytics and computerised adaptive testing show that more dynamic, process-oriented assessment is possible, while automated scoring systems highlight both the scalability and the risks of current approaches. At policy level, the OECD and UNESCO keep calling for competency-based, ethical and transparent systems. Institutions remain slow to adapt.

If this continues, assessment risks becoming ever more performative, while students become more strategic and less transparent.

Final thought: the real issue is not that students are using AI. It is that they may already be learning and evolving faster than the systems meant to measure them.

Beyond Mock Exams: Audio Briefings for the AI Era

Mock exams are not a tenable method of assessment in the age of AI and digitalisation. As an educator in multilingual education and AI-assisted pedagogy, I am challenging the memorisation paradigm that has dominated our classrooms for too long. Mock exams belong to a different era, rooted in the standardisation and industrial paradigm that treated education like assembly-line production. Here is why I reject them, and what I do instead.

Why mock exams fail

Mock exams promote rote cramming and turn students into prisoners of repetition. They kill cognitive dynamism and ignore how multilingual skills, such as contextual fluency and cultural adaptation, demand real-world application rather than one-shot tests from an outdated industrial model.

My approach: progressive mastery, in class and remotely

I favour continuous activities and mini-projects that build competencies situationally. Students apply their multilingual skills through collaborative tasks, simulations and AI-enhanced workflows, developing a deep, layered understanding along the way.

The innovation: NotebookLM audio guides

Today I used NotebookLM to create an audio overview of the final exam structure: an elaborate narrative linking each question to the full network of lectures. Students engage multisensorially, listening, associating content (the module on multilingual practices and ethics, for example) and reflecting. This immersive preparation boosts retention without a single mock exam.

In the AI era of multilingual education, tools like these augment cognition, reduce anxiety and spark motivation. Yet existing structures and policies, especially those plagued by micro-management and control-mania, do not let such illuminating methods be nurtured and implemented.

How to Translate Website Images

A short tutorial on translating the images on a website – a small, easily forgotten part of localising a site properly.

Making a WordPress Site Multilingual with Weglot

A walkthrough of turning a WordPress website multilingual with Weglot – useful for translators who want to see how website localisation tools work in practice.

Building a Multilingual Elementor Site with Polylang

A tutorial on making an Elementor website multilingual with Polylang – another practical example of the localisation tooling translators are now expected to understand.

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Toxic Academic Cultures and the Faculty They Suffocate

Certain variables poison an academic context and, if that context refuses to accommodate change, undermine its future. Among them:

• politics and politically oriented motives;
• negative competition and insecurity;
• indoctrination without formal, macro-level knowledge and know-how;
• centralising one's own thoughts, and being stuck in one place for years believing that the university culture one learnt is the only approach that exists in academia.

Academic contexts and practices change continually, and so do the needs around them: student profiles and needs, workplace needs, and other extra-academic demands. If none of this is accommodated, new faculty, the fresh blood in the system, will find it hard, even impossible, to breathe and unleash their potential.

A Failure of Leadership

That kind of work atmosphere reflects a lack of leadership. It stresses errors, punitive methods, unnecessary warnings and constant policing. It runs a factory model of shifts, as if everybody should imitate the administrators' nine-to-five, when faculty in academia do not need to abide by that pattern. Administrators are paid additional stipends or fees to do so; faculty are not.

Such work cultures do everything they can to "keep faculty busy", to the point of exploiting them. Where else on earth, in the GCC region or beyond, do faculty do more than two, or at most three, invigilation shifts? Usually administrative clerks handle invigilation, or faculty and others are paid to do it.

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Research on using dialogic competence in debates (classroom environments)

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