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Study Skills for Neurodivergent Students

Logical-mathematical Intelligence

  • Strengths: Excel in pattern recognition, problem-solving, and quantitative analysis.

  • Study approaches: Use practice problems, create flowcharts and diagrams, connect concepts to real-world applications, participate in logic-based games.

  • Tools: Math apps, educational simulations, interactive quizzes with feedback.

  • Careers: Engineer, mathematician, accountant, computer scientist, researcher, pilot, statistician, actuary.

Study Skills for Logical-mathematical Intelligence

  • Organise information: Categorise facts, use flowcharts to track processes, and build concept maps to connect ideas logically.

  • Practice with purpose: Identify patterns in past paper questions, develop problem-solving strategies, and analyse your mistakes for improvement.

  • Quantify your progress: Set realistic goals, track time spent studying, and reward yourself for achieving milestones.
  • Chart your course: Create flowcharts or timelines to visualise study schedules, use tables and graphs to organise data, and prioritise tasks based on urgency and importance.

  • Systematic success: Develop a step-by-step study plan for each topic, track your progress with checklists and charts, and set realistic goals with achievable milestones.

  • Harness the power of numbers: Number your notes and reference pages, utilise numbering systems for categorisation, and use time management tools like the Pomodoro Technique.
  • Break down problems: Divide complex tasks into smaller, manageable steps, focus on completing one step at a time, and reward yourself for progress.

  • Analyse distractions: Identify what breaks your focus, create strategies to eliminate or minimise them (e.g., block social media, use noise-cancelling headphones).

  • Challenge yourself: Engage in puzzles, brain teasers, or logic games to train your focus muscles, apply problem-solving skills to stay engaged with challenging material.
  • Outline and categorise: Organise notes using clear headings, flowcharts, and bulleted lists.

  • Colour-code information: Highlight key terms, categorise concepts by colour, and create visually distinct sections.

  • Utilise graphic organisers: Use mind maps, concept maps, and timelines to visually represent relationships between ideas.

  • Focus on problem-solving: Analyse case studies, apply concepts to real-world scenarios, and seek opportunities to practice applying knowledge.
  • Organise with logic: Develop a flowchart of your argument, categorise evidence, and ensure logical progression of ideas.

  • Analyse and dissect: Evaluate sources critically, identify strengths and weaknesses of arguments, and present your own with logical reasoning.

  • Use data to your advantage: Integrate statistics, graphs, or quantitative evidence to support your claims and strengthen your essay's foundation.

  • Proofread with precision: Eliminate errors in grammar, logic, and formatting, ensuring your essay is well-structured and error-free.
  • Organise your findings: Categorise sources by theme, create matrices to compare studies, and develop logical frameworks for integrating information.

  • Evaluate with precision: Analyse research methods, assess data validity, and identify potential biases in sources.

  • Utilise citation management tools: Explore software like Mendeley or Zotero to organize references, track progress, and generate citations effortlessly.

  • Visualise connections: Create mind maps or flowcharts to represent relationships between key findings, identify gaps in research, and develop your own arguments.

Tools and Apps

Problem-Solving:

  • Project Euler: Online platform with challenging maths problems ranging from easy to expert level.
  • Brilliant: Interactive platform with bite-sized challenges and explanations relevant to university-level math and science.
  • Wolfram Alpha: Computational knowledge engine that can solve and explain complex mathematical problems.
  • Desmos: Graphing calculator app with advanced features for visualisation.

Coding & Programming:

  • Codecademy: Learn coding languages through interactive projects.
  • Udacity Nanodegrees: Specialised online courses with industry-relevant projects in data science, web development, and other high-demand fields.
  • GitHub Student Pack: Free access to developer tools and resources, including collaboration features and private repositories.
  • Kaggle: Platform for data science competitions and learning, offering datasets and tutorials.

Data Analysis:

  • R/Python: Powerful programming languages commonly used in academic research and data analysis.
  • Jamovi: User-friendly statistical software with a beginner-friendly interface.
  • Tableau Public: Free data visualisation tool for creating interactive dashboards and report