Terminology - adaptive-learning/flocs GitHub Wiki

The purpose of this page is to make sure we all know and agree on the semantics of terms we use throughout the system, which might be otherwise ambiguous.

To Be Defined:

• flow, flow-difficulty, task (in)efficiency
• skill
• credits, levels

Concept

• ?? a feature of both students and tasks which influence the solving process
• concepts of a student determine her skill
• concepts of a task determine its difficulty
• division:
  • block concepts (forward, turn, repeat block, while block, etc.)
  • game concepts (maze, workspace, run, block limit, colors, pits, tokens)
  • other suggestions: nested loops, bias (general problem solving concept)
  • binary (block, game) vs. continuous (loops, nested loops, problem solving, ...)?

Concept strength

• TODO: define properly
• ?? for both tasks and students, how much is the concept learnt or which level of mastery of this concept the task requires
• interpretation for student:
  • ~ -1 ... the concept is not learnt yet
  • ~ 0 ... the concept is ready to learn
  • ~ +1 ... the concept is already mastered

Flow

• TODO: define properly (for given student s and task t)
• interpretation:
  • ~ -1 ... too difficult task (leading to frustration)
  • ~ 0 ... optimally difficult task (leading to flow)
  • ~ +1 ... too easy task (leading to boredom)

Time-difficulty

• definition: log-time of the solving time of given task if solved by an average user
• the group invariance property is important
• to resolve:
  • who is an average user (my guess: if we sort all the users by the solving time, it's the middle one; but what if more than half of the users is not able to solve the task at all?)
  • average user in our system, in this moment ?
  • new users vs. all users vs. taking a time spent in our system into account ?