2012-13-school-data-with-affect

This is the ASSISTment data for the school year 2012~2012 with affect predictions.

For a while the data was stored here (https://drive.google.com/file/d/0BxCxNjHXlkkHczVDT2kyaTQyZUk/edit?usp=sharing) but now store the data here 

If you use the columns related to affect please cite the following paper.

Pardos, Z.A., Baker, R.S.J.d., San Pedro, M.O.C.Z., Gowda, S.M., Gowda, S.M. (2013) Affective states and state tests: Investigating how affect throughout the school year predicts end of year learning outcomes. Proceedings of the 3rd International Conference on Learning Analytics and Knowledge, 117-124

If you are not using the affect column please acknowledge ASSISTment with a citation to the following paper.

Feng, M., Heffernan, N.T., & Koedinger, K.R. (2009). Addressing the assessment challenge in an Intelligent Tutoring System that tutors as it assesses. The Journal of User Modeling and User-Adapted Interaction.19, 243-266. (Based on CP15) Best Paper of the Year (See Award #20 above). Mentioned in National Ed. Tech Plan (See Award 19 above).

Column Headings

• problem_log_id

  • Unique ID of the logged actions.

• skill

  • Skill name associated with the problem (different skills are in different rows).

• problem_id

  • The ID of the problem.

• user_id

  • The ID of the student doing the problem.

• assignment_id

  • Two different assignments can have the same sequence id. Each assignment is specific to a single teacher/class.

• assistment_id

  • The ID of the ASSISTment. An ASSISTment consists of one or more problems.

• start_time

  • Timestamp when the problem starts.

• end_time

  • Timestamp when the problem ends.

• problem_type

  • choose_1: Multiple choice (radio buttons)

  • algebra: Math evaluated string (text box)

  • fill_in: Simple string-compared answer (text box)

  • open_response: Records student answer, but their response is always marked correct

• original

  • 1 = Main problem

  • 0 = Scaffolding problem

• correct

  • 1 = Correct on first attempt

  • 0 = Incorrect on first attempt, or asked for help.

• bottom_hint

  • Whether or not the student asks for all hints.

• hint_count

  • Number of hints on this problem.

• actions

  • Every action on this problem.

• attempt_count

  • Number of student attempts on this problem.

• ms_first_response

  • The time in milliseconds for the student's first response.

• tutor_mode

  • tutor, test mode, pre-test, or post-test

• sequence_id

  • The content id of the problem set. Different assignments that assign the same problem set will have the same sequence id.

• student_class_id

  • The class ID.

• position

  • Assignment position on the class assignments page.

• type

  • Linear - Student completes all problems in a predetermined order.

  • Random - Student completes all problems, but each student is presented with the problems in a different random order.

  • Mastery - Random order, and student must "master" the problem set by getting a certain number of questions correct in a row before being able to continue.

• base_sequence_id

  • This is to account for if a sequence has been copied. This will point to the original copy, or be the same as sequence_id if it hasn't been copied.

• skill_id

  • ID of the skill associated with the problem (different skills are in different rows).

• teacher_id

  • The ID of the teacher who assigned the problem.

• school_id

  • The ID of the school where the problem was assigned.

• overlap_time

  • The time in milliseconds for the student's overlap time.

• template_id

  • The template ID of the ASSISTment. ASSISTments with the same template ID have similar questions.

• answer_id

  • The answer ID for multi-choice questions.

• answer_text

  • The answer text for fill-in questions.

• first_action

  • The type of first action: attemp or ask for a hint.

• problemlogid

  • Unique ID of the logged actions.

• Average_confidence(FRUSTRATED)

  • Predicted Frustration of student for the problem. Value close to "0" being less frustrated and close to "1" being more frustrated.

• Average_confidence(CONFUSED)

  • Predicted Confusion of student for the problem. Value close to "0" being less confused and close to "1" being more confused.

• Average_confidence(CONCENTRATING)

  • Predicted Engaged Concentration of student for the problem. Value close to "0" being less concentrated and "1" being more concentrated.

• Average_confidence(BORED)

  • Predicted Boredom of student for the problem. Value close to"0" being less bored and "1" being more bored.

Here's the code and data for the current affect detectors:

https://drive.google.com/folderview?id=0B9MXO4ELrnzyUjdlVE1PWElHSE0&usp=sharing