ALLT 2024 Professional Development Training

Professional Development courses for ALLT 2024 will be provided soon

Course Description: "Practical Computational Text Analysis" is a comprehensive 3-hour course designed to familiarize students with the basics of computational text analysis. The course is structured into three key sections. The first part provides a theoretical introduction to foundational computational methods used in text analysis, including concordance analysis, word frequency analysis, and topic modeling. This is followed by a demonstration of "Voyant Tools," an online platform that enables students to apply these methods to their own texts. The final segment is a hands-on practical session where students will engage in the computational analysis of specific text corpora. Throughout the course, students will gain a solid understanding of textual computational methods, learn to utilize Voyant Tools for their analyses, and acquire practical experience in handling real-world text data. This course aims to equip students with essential skills in computational text analysis, preparing them for further academic and professional applications in this field.
Course Aim: The aim of the "Practical Text Analysis" course, especially relevant to language teaching, is to equip language educators and students with the essential skills and tools for computational text analysis. This course focuses on understanding and utilizing computational methods such as concordancing, word frequency analysis, and topic modelling to enhance language learning and teaching. By learning how to use "Voyant Tools," an online platform for text analysis, educators can better analyze language usage, identify linguistic patterns, and develop more effective teaching materials. The hands-on session with specific text corpora will allow participants to apply these methods in real-world language teaching contexts, facilitating the creation of data-driven language learning activities and resources. Ultimately, this course aims to empower language teachers with the knowledge and skills to integrate computational text analysis into their teaching practices, thereby enriching the language learning experience for their students.
Anticipated Outcomes

The objective of the "Practical Text Analysis" course, particularly relevant to language teaching, is to equip language educators and students with essential skills and tools for computational text analysis. This course specifically focuses on comprehending and applying computational methods, such as concordancing, word frequency analysis, and topic modeling, to enhance language learning and teaching.

By mastering the use of "Voyant Tools," an online platform for text analysis, educators can analyze language usage, identify linguistic patterns, and develop more effective teaching materials. The hands-on session with specific text corpora allows participants to apply these methods in real-world language teaching contexts, facilitating the creation of data-driven language learning activities and resources

Ultimately, the course aims to empower language teachers with the knowledge and skills to seamlessly integrate computational text analysis into their teaching practices, enriching the language learning experience for their students.

The anticipated outcomes of the "Practical Text Analysis" course, particularly in the context of language teaching, include:

  • Enhanced Analytical Skills: Participants will develop a strong foundation in computational methods such as concordancing, word frequency analysis, and topic modeling—essential for deep linguistic analysis and understanding language patterns.
  • Proficiency in Digital Tools: Educators and students will gain proficiency in using "Voyant Tools," enabling them to integrate technology into language teaching and learning effectively.
  • Improved Material Development: Armed with acquired knowledge, language teachers can create more engaging and effective teaching materials, tailoring content to address specific linguistic features or learner needs.
  • Data-Driven Teaching Approaches: The course enables educators to adopt data-driven approaches in language teaching by analyzing real-world text corpora, allowing them to base teaching strategies on actual language usage patterns.
  • Innovative Teaching Strategies: Exposure to computational text analysis encourages teachers to explore innovative teaching strategies, incorporating findings from analyses into classroom activities for more interactive and relevant learning experiences.
  • Research Opportunities: For those involved in academic research, the course opens up new avenues for investigation in the field of language education, facilitating more empirical and data-backed research studies.
  • Enhanced Student Engagement: By integrating technology and data-driven insights into language teaching, educators can create a dynamic and engaging learning environment, fostering increased student interest and participation.
Trainer Bio George Mikros is currently a Professor and the Coordinator of the MA Program in Digital Humanities and Societies at the Department of Middle Eastern Studies at Hamad Bin Khalifa University in Qatar. Prior to this role, from 1999 to 2019, he served as a Professor of Computational and Quantitative Linguistics at the University of Athens, Greece, where he founded and became the Director of the Computational Stylistics lab. Since 2013, he has also held the position of Adjunct Professor at the Department of Applied Linguistics at the University of Massachusetts, Boston, USA.
Professor Mikros has authored 5 monographs and over 100 papers published in peer-reviewed journals, conference proceedings, and edited volumes. Since 2007, he has been elected as a Member of the Council of the International Association of Quantitative Linguistics (IQLA). During the period from 2018 to 2021, he served as its president. He has been a keynote speaker at numerous international conferences, workshops, and summer schools focusing on Digital Humanities, AI, Forensic Linguistics, and Quantitative Linguistics. His primary research interests include computational stylistics, quantitative linguistics, computational linguistics, and forensic linguistics.
Course Description: Contract cheating refers to a significant issue where students engage in the practice of purchasing assignments from external sources. It poses a challenge for educators, jeopardizing academic integrity. The objective of this course is to discuss the root causes of contract cheating and possible mitigation techniques. We will illustrate how AI can be used to mitigate the impacts of contract cheating. Specifically, we will demonstrate AI-based techniques to support the learning process of students but also to detect contract cheating.
Course Aim: Addressing contract cheating through root cause analysis, mitigation techniques, and leveraging AI for enhanced learning and detection.
Anticipated Outcomes
  • Understand the reasons for contract cheating.
  • Identify mitigation techniques for contract cheating.
  • Use AI to detect and prevent contract cheating.
Trainer Bio Dr. Ahmad Samer Wazan is an Associate Professor at Zayed University, where he conducts research in trust management, access control, security, and artificial intelligence. He led a project from 2007 to 2011 that defined a new trust model for the X.509 standard, which was subsequently included in the 2016 edition of the standard. Wazan also participated in developing the first verifiable credential system with researchers from the UK and France. Recently, he proposed a new command called "sr" (switch role) to replace the command "sudo" in a Linux environment. Dr. Wazan previously worked with the founder of souq.com as a web developer and security analyst from 2003 to 2006 and was awarded the prize for the best employee in 2004. He is currently on secondment from Toulouse University to Zayed University
Course Description:

In this dynamic workshop, participants will explore the transformative role of Large Language Models (LLMs) in English Language Teaching (ELT). As AI continues to revolutionize various sectors, its impact on language learning is both profound and promising. This session will delve into practical strategies for integrating AI tools into ELT, focusing on how LLMs can personalize learning experiences, provide instant feedback, and create interactive, engaging content for learners.

Attendees will get hands-on experience with cutting-edge AI applications, learning to harness these tools to support language skill development in areas such as vocabulary enhancement, grammar, reading comprehension, and conversational fluency. The workshop will also address challenges such as ensuring pedagogical effectiveness and maintaining human interaction in AI-assisted language learning environments.

Ideal for ELT professionals, this session promises to be a blend of theoretical insights and practical applications, equipping educators with the knowledge and skills to effectively incorporate AI into their teaching methodologies.

Course Aim: This workshop aims to empower English Language Teaching professionals by demonstrating the effective use of Large Language Models in enhancing language learning. Through practical demonstrations and interactive activities, participants will learn to integrate AI tools into their teaching methodologies, focusing on personalization, instant feedback, and interactive content creation. This will ultimately improve learner engagement and proficiency in English language skills while addressing the challenges of maintaining pedagogical integrity in AI-enhanced environments.
Anticipated Outcomes
  • Comprehensive understanding of integrating large language models in English language teaching.
  • Enhanced skills in incorporating AI into language instruction for greater personalization and interactivity.
  • Improved ability to develop AI-driven lesson plans.
  • Increased learner engagement and motivation through innovative teaching methods.
  • Enhanced proficiency in utilizing AI tools for effective language skill development.
  • Insights into balancing technology with traditional teaching methods for optimal learning outcomes.
  • Strategies for maintaining a harmonious blend of AI and human interaction in language education.
Trainer Bio Michael Pazinas makes significant contributions to the field of educational innovation and digital learning as a Specialist in Pedagogical Innovation and Effectiveness at Zayed University's Center of Educational Innovation. He is involved in researching and fostering creativity and innovation in higher education pedagogy. Recognized for his expertise and commitment, he has earned the title of Senior Fellow from the Higher Education Academy, UK. In his multifaceted role, Michael is the Lead Apple Professional Learning Specialist in the Middle East, an Apple Distinguished Educator, and a certified Apple Sales Trainer. He plays a crucial part in the recruitment and training of APLSs throughout the region, crafting professional learning programs and leading training sessions in Europe and the Gulf. In 2018, Michael initiated the Abdul Wahid Al Rostamni Inclusive Learning Center at Zayed University, innovatively using Apple technology for inclusive education. Michael has been serving as the Program Director for Creativity and Innovation at Sandooq Al Watan, directing national projects for UAE youth. Currently, he is deeply engaged in postgraduate research at Lancaster University, UK, working on tools to assess digital agency and AI in educational settings.
Course Description:

This course will present a range of innovative speaking activities that can be adapted for various needs and teaching contexts, in order to stimulate teachers to experiment with a wide range of activities to improve their learners’ speaking skills, both in traditional and online or hybrid learning contexts. Special attention will be paid to the concepts of communicability, intelligibility, and oracy (the ability to combine fluency with accuracy and to be more flexible), and the ways that learners can be empowered to use spoken language to express themselves more creatively, effectively, and confidently.

The use of authentic videos of actual learners doing speaking activities will also be discussed, along with the practicalities of teaching speaking inside and outside classrooms and online with classes of all kinds, with a focus on real-world contexts and real-world students. Participants will have the opportunity to take part in practical activities using not only traditional but also digital tools.

Course Aim: This course aims to highlight how, through creative and meaningful activities, learners can be motivated to produce authentic and communicative spoken discourse, even at low levels. Participants will be encouraged to rethink some of the ways that they have approached speaking in class in order to take advantage of new digital tools that are now widely available.
Anticipated Outcomes The participants will be shown and have the opportunity to participate in a wide range of speaking activities, each designed to practice spoken discourse in an authentic manner (i.e., activities that have a real communicative purpose, not just a didactic end). These activities will help participants reevaluate the way they currently teach and assess and also provide them with some activities and tools that they can immediately apply to their classrooms.
Trainer Bio

Thomas Wulstan Christiansen is an associate professor in English Language and Translation at the University of Salento (Italy) and the Director of the University Language Centre. Of Danish-English heritage and originally from Birmingham, England, he has been based in southern Italy since he graduated in 1987.

He has taught at various higher education institutions in Apulia (Italy), Poland, and the UK. He is also a language teaching and testing consultant. In this capacity, he has worked widely for prestigious international examination boards in Italy, as well as Albania and Kosovo. He has worked in specialist work groups drafting revisions to some of the most popular English-language exams in the world and has presented numerous seminars and webinars on a wide range of subjects related to testing, language teaching, exam preparation, and the applications of AI to language teaching.

Course Description:

Writing a text with a well-reasoned conclusion can be challenging for students. How and where to begin? Argument mapping is a technique that can help. An argument map is a diagram or plan that you create before you start writing, and it can help you overcome writer’s block. An argument map allows you to explore the structure of an argument. Claims are depicted as boxes with text, and these boxes are connected by lines that represent ‘support’ and ‘oppose’ relations. Argument mapping not only helps you organize your own thoughts, but it can also help you understand arguments put forward by other people. This, in turn, may allow you to better appreciate both the strengths and weaknesses of their arguments.

Course Aim: The aim of this course is to introduce the technique of argument mapping and digital tools for argument mapping through practical activities and case studies. This will help in solving problems that involve drawing reasoned conclusions. For language teaching, argument mapping provides a practical technique for helping students with writing and understanding reasoned conclusions.
Anticipated Outcomes By the end of this session, you will be able to:
  • describe the key ingredients of an argument map;
  • start from an argument map and write argumentative text based on the map;
  • create an argument map based on someone else’s writing;
  • explain how digital argument mapping extends our natural capabilities; and explain the role of argument mapping in relation to Generative AI.
Trainer Bio

Dr. Paul Piwek, an Associate Professor at the Open University, brings a deep interest in language and logic to the world of Artificial Intelligence. He earned his PhD from the Institute for Perception Research (Eindhoven University and Philips Research), focusing on the intersection of these disciplines. His recent project, "Opening Up Minds" (mcs.open.ac.uk/pp2464/Opening_Up_Minds/), aims to develop AI tools that help navigate conversations, even across ideological divides. This work addresses a pressing societal challenge, seeking to bridge communication gaps and foster mutual understanding. He has published his work in journals such as Artificial Intelligence and Synthese, as well as at conferences like ACL and COLING. He has developed courses at the Open University, including the popular free "Digital Thinking Tools" (open.ac.uk/digital-thinking) course co-authored with Richard Walker. He is the Public Understanding and Schools Liaison Officer for the Society for the Study of Artificial Intelligence and Simulation of Behaviour (AISB; aisb.org.uk).