Mastery Learning & Talent Development

Mastery Learning

Historical experience and evidence suggests the traditional "one size fits all" approach to education has failed. Both the "Conventional Model" (students learn from a teacher in classrooms with 30 or so other students, periodically taking assessment tests) and the "Mastery Learning Model" (conventional model plus a feedback loop to bring more students up to foundational mastery) only benefit a small subset of students.

The DSA Mastery Learning concept guides our designing curriculum, setting learning goals, and assessing student learning using the DSA Online Education Platform by incorporating specifically trained AI Coaches to emphasize individualized instruction and provide students with additional support until they fully grasp a concept before moving on.

Our objective is to ensure that all students achieve mastery of subject matter at their own pace in their own unique learning style.

AI Coach / Tutor

Note: The AI Coach / Tutor's are currently under development and will be available soon.

DSA has modified and beta tested the traditional human tutoring model (students learn the subject matter with a human tutor for one to three students at a time, with testing and a feedback loop for mastery) to incorporate an AI Coach / Tutor available 24/7 - with an online education platform with courses and modules, tests and quizzes for instant feedback - for cost-effective high-quality education.

The AI Coach provides students with additional support until they master a concept before moving on. This approach aims to ensure that all students achieve understanding at their own learning style and pace.

The AI Coach, while trained on specific subject matters, emphasizes mastery of fundamentals including key conceptual frameworks, non-linear, system level and critical thinking skills, data interpretation skills, and scenario planning skills. In other words, applied data science in the real world as opposed to research data science in the academy that emphasizes theory over practice.

The AI Coach is continuously improving and in the near future will adapt to each students individual learning style.

Applied vs. Research Data Science

There is a significant difference between applied data science in the real world as opposed to research data science in the academy that emphasizes theoretical processes over real-world practice. Note that research data scientists can massively improve their craft by learning applied data science.

DSA Mastery Learning and AI Coaching focuses on applied data science (that borrows some concepts from research data science) for the professional data science practitioner.

This means including both inductive and deductive logic, mastering myriad conceptual frameworks, non-linear thinking, system level thinking, goal setting skills, strategy and tactical skills, scenario planning skills, leadership, advanced decision-making skills, risk assessment and mitigation skills, and navigating complexity with imperfect information without blowing up.

Although both theory and practice are important, there is a big difference between them. A wise man once stated: "Beware of defending theories masquerading as reality in untrained and undisciplined minds."