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 is stored 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 ASSISTments 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