The culture of optimization  refers to current societal trends or mindsets where there is a strong emphasis on continuously improving and maximizing efficiency, performance, and productivity.   This concept is prevalent in technology, business, and personal development — and also in education, including language education.

As I discuss in my chapter on the history of listening instruction in the Wiley Handbook of Second Language Listening, we might see this as a kind of reversion to behaviorism, which dominated education in the 1960s.  Rather than adhering to principles of holistic language growth, which includes important aspects of human well-being, such as mental health and work-life balance, the relentless focus on optimization can sometimes single-mindedly emphasize only measurable aspects of performance in the immediate term.

In listening instruction, this culture of optimization is realized through behavioral modification and through technological mediation.

In terms of behavioral modification, there are a number of systems that I have seen employed in educational contexts:

  1. Positive Reinforcement: Using rewards to encourage desired behaviors, such as good study habits, attendance, and participation. Rewards can be tangible (e.g., stickers, certificates) or intangible (e.g., praise, recognition).
  2. Negative Reinforcement and Punishment:Implementing consequences to discourage undesired behaviors, such as missed assignments or sub-standard efforts. Negative reinforcements might involve loss of privileges (e.g. participation in fun activities) or some kind of mild “public shaming”.
  3. Feedback Systems:Providing regular, specific feedback to students about their performance to guide their learning processes. Immediate feedback can help students understand what they did right or wrong and how to improve.
  4. Data-Driven Decision Making: Using data to track student progress and adjust teaching strategies, input selection, and task design accordingly. This involves monitoring student performance through assessments and using that data to identify areas where students need additional support or enrichment.
  5. Behavioral Tracking:Monitoring and recording student behaviors to identify patterns and intervene when necessary. This can include tracking attendance, assignment completion, and participation rates.
  6. Self-Monitoring Techniques:Encouraging students to monitor their own behaviors and progress. This can involve setting personal goals, self-assessment, and reflection activities to help students take ownership of their learning.
  7. Gamification:Incorporating game-like elements into the learning process to motivate students. This can include points, badges, leaderboards, and other game mechanics that make learning more engaging and fun.
  8. Structured Environments:Creating structured and predictable classroom environments that promote positive behaviors. This can involve clear rules, routines, and expectations that help students know what is expected of them.
  9. Personalized Learning Plans:Developing individualized learning plans based on student data to address specific needs and strengths. Personalized plans can help optimize learning by targeting instruction to the student’s unique learning style and pace.
  10. Social and Emotional Learning (SEL):Incorporating SEL programs that focus on developing students’ self-awareness, self-regulation, social skills, and responsible decision-making. SEL programs can help create a positive learning environment and support students’ overall well-being.

In terms of technological mediation there are multiple uses of technology as a means of delivering input, facilitating and enhancing the learning of listening skills. It involves leveraging various technological tools, platforms, and resources, allowing learners to engage with authentic spoken language input in interactive and dynamic ways.

Technological advances, from audio recorders to language laboratories, have long been part of the teaching, and CALL (Computer Assisted Language Research) research and initiatives related to listening have been prolific since the 1960s (Bax, 2003). Progress and integration of technology into the teaching of listening have accelerated dramatically since the start of the 2020s. It is currently assumed that any formal listening course will include the following kinds of mediation (Rost 2024, Chapter 5):

  1. Access to a wide range of authentic and age/proficiency level listening materials, audio and video-based, for streaming or download, from a variety of genres.
  2. Online learning platforms that allow a student to have access to formal instruction and teacher interaction.
  3. A multitude of streaming options, including variable speeds, captioning, and subtitling, in the viewer’s L1 or in the TL, accessible study notes, and interactive transcripts.
  4. Interactive listening activities, consisting of comprehension checksmultiple-choice quizzesgap-fill exercises, and dictation exercises, often with immediate assessment and feedback.
  5. Mobile devices have made language learning more convenient and accessible. Mobile apps and platforms offer anytime-anywhere listening practice.
  6. Collaborative learning tools, virtual classrooms, discussion forums, and social media groups to foster a sense of community and allow for the sharing of learning experiences.
  7. New technologies support multimodal interaction, allowing learners to practice listening through a variety of modalities, including text, speech, images, and multimedia content that can be adjusted to an individual learner’s preference.
  8. Evolving technologies like Virtual Reality (VR) and Augmented Reality (AR) offer immersive virtual environments that simulate real-life listening situations, allowing students to practice their skills in context.
  9. Artificial Intelligence (AI)-powered language learning platforms can personalize instruction based on students’ individual learning needs and preferences.
  10. Conversation AI Bots can provide limitless opportunities for conversation practice. As bots utilize natural language processing (NLP) algorithms to understand learners’ input and generate voice or text responses, they can engage learners in topic-oriented, level-appropriate conversation, controlled for speed and complexity, and provide feedback on pronunciation, grammar, and vocabulary.

Article copyright © Michael Rost, 2024


Aleman-Centeno, J.R. (1982). Foreign language instruction for listening comprehension using computer-directed audio-visual media. Ph.D. dissertation. University of Iowa. Dissertation Abstracts, 43.

Bax, S. (2003). CALL—past, present and future. System31(1), 13-28.

Chen, X., Gao, Y., Tang, W., Guan, J., & Ryoo, J. (2024). AI Application in Foreign Language Literature: ChatGPT’s Impact and Skill Enhancement. European Journal of Contemporary Education and E-Learning2(2), 3-18.

Rost, M. (2024). Teaching and researching listening, 4th edition. Routledge.

About The Author

, The culture of optimization: Maximizing listening performance, Lateral Communications
Michael Rost, principal author of Pearson English Interactive, has been active in the areas of language teaching, learning technology and language acquisition research for over 25 years. His interest in bilingualism and language education began in the Peace Corps in West Africa and was fuelled during his 10 years as an educator in Japan and extensive touring as a lecturer in East Asia and Latin America. Formerly on the faculty of the TESOL programs at Temple University and the University of California, Berkeley, Michael now works as an independent researcher, author, and speaker based in San Francisco.