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Tower of Hanoi Task (TOH)
(German instructions)
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last updated: 04-10-2024 by K. Borchert (katjab@millisecond.com) for Millisecond Software, LLC
Script Copyright © 04-10-2024 Millisecond Software
German translation provided by K. Borchert for Millisecond Software
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BACKGROUND INFO
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This script implements a computerized version of the Tower of Hanoi Task (TOH), a disk transfer task with 3
equally sized pegs, as described by Humes et al (1997). The TOH is considered a test of executive functioning
with a focus on planning abilities.
Researchers can select to run the task with an absolute screen size to ensure that distances
stay the same across devices. The default sizing settings are optimized for ipad touchscreens.
See section Editable Parameters for more info.
Reference:
Humes, G. E., Welsh, M. C., Retzlaff, P., & Cookson, N. (1997). Towers of Hanoi and London:
Reliability and Validity of Two Executive Function Tasks.
Assessment (Odessa, Fla.), 4(3), 249–257.
https://doi.org/10.1177/107319119700400305
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TASK DESCRIPTION
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Participants are asked to arrange up to five disks of varying sizes on three different pegs
in a specific goal pattern in as few moves as possible and observing two movement rules:
"Only move the top disk" and "bigger disks may not be placed on top of smaller disks".
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DURATION
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the default set-up of the script takes appr. 10 minutes to complete
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DATA OUTPUT DICTIONARY
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The fields in the data files are:
(1) Raw data file: 'towerofhanoi_raw*.iqdat' (a separate file for each participant)
build: The specific Inquisit version used (the 'build') that was run
computer.platform: the platform the script was run on (win/mac/ios/android)
date, time: date and time script was run
subject, group: with the current subject/groupnumber
session: with the current session id
//Screen Setup:
(parameter) runAbsoluteSizes: true (1) = should run absolutely sized canvas (see parameters- canvasHeightMM)
false (0) = should use proportionally sized canvas (uses width = 43*screenHeight)
canvasAdjustments: NA: not applicable => parameters- runAbsoluteSize was set to 'false'
0: parameters- runAbsoluteSize was set to 'true' and screen size was large enough
1: parameters- runAbsoluteSize was set to 'true' BUT screen size was too small and
adjustments had to be made
activeCanvasHeightMM: the width of the active canvas (by default: lightGray area) in mm
activeCanvasWidthMM: the height of the active canvas in mm
display.canvasHeight: the height of the active canvas in pixels
display.canvasWidth: the width of the active canvas in pixels
pxPerMM: the conversion factor to convert pixel data into mm-results for the current monitor
(Note: the higher resolution of the current monitor
the more pixels cover the same absolute screen distance)
This factor is needed if you want to convert pixel data into absolute mm data or the other way around
runPractice (parameter): 1 = a practice session was run; 0 = otherwise
blockCode, blockNum: the name and number of the current block (built-in Inquisit variable)
trialCode, trialNum: the name and number of the currently recorded trial (built-in Inquisit variable)
Note: trialNum is a built-in Inquisit variable; it counts all trials run; even those
that do not store data to the data file such as feedback trials. Thus, trialNum
may not reflect the number of main trials run per block.
problemCount: tracks the number of problems run
problemNumber: Current problem number (by default: 1-12)
goalstateCategory: "tower" vs. "flat"
nDisks: stores the number of disks present in the current problem
targetMoves: Number of minimal moves to solve the current problem
targetAchieved: Returns 1 as soon as the subject has successfully reached a given problem's target / goal state.
Otherwise 0.
subjectMoves: Number of subject-performed moves for the current problem.
Note: each rule violation counts as one extra move in this script
excessMoves: Returns the difference between number of moves performed by the subject ('subjectmoves')
and the number of target moves for a given problem.
consecutiveCorrect: counts the number of consecutive correct solutions for the same problem
stopTask: 1 = the task should be terminated at this point (values.success = 0 at end of all attempts for the current problem)
0 = otherwise
success: 1 = the current problem was solved correctly according to definition of success
(default: success (test)= problem solved correctly twice in consecutive attempts)
0 = the current problem has not (yet) been successfully solved
achievementScore: Score awarded for solving the current test problem if values.success = 1.
see expressions.scoring
totalScore: Score achieved across the whole set of test problems.
In this script: Max is 72
violation: 0 = no rule was violated with the currently recorded move
1 = rule 1 was violated ('no larger disk onto smaller disk')
2 = rule 2 was violated ('only top disk can be moved')
(if rule 1 AND rule 2 are violated in the same move, only rule violation 2 is noted.
The violations count as a single violation in this script)
countViolationsProblem: counts the number of rule violations per problem
firstMoveTime: Returns the time (in ms) elapsed between initial presentation of
the goal configuration and the initialization of the subject's first valid
move. Sometimes also referred to as "planning time" or simply
"latency". Note: Measure is computed separately for each problem attempt.
solutionTime: Returns the time (in ms) elapsed between initial presentation of
the goal configuration and a subject's successful solution or problem termination.
Note: Measure is computed separately for each problem attempt.
executionTime: Computed as solutiontime - firstmovetime. Note: Measure is
computed separately for each problem attempt.
tChoiceStart: Absolute start time for trial.choice in ms. May be used to derive
additional measures during data analysis (e.g. mean move time).
tChoiceend: Absolute end time for trial.choice in ms. May be used to derive
additional measures during data analysis (e.g. mean move time).
totalCompletionTime: cumulative solution times across all problem sets attempted
latency: the latency of the current response in ms (or if no response: trialduration)
response: response made (the peg that was moved to)
trial.choice.lastDropSource: the last moved disk (d1, d2, d3, d4, or d5)
trial.choice.lastDropTarget: the last peg that a disk was moved to (apeg, bpeg, cpeg)
moveString: Text string containing a record of performed moves. E.g. "1apeg,"
indicates that disk1 (the smallest) was moved to pegA (the left one).
A rule violation is expressed as "rule1violation (2bpeg)" => disk2 was moved onto a smaller disk onto b-peg
topInA: Returns the disk number (1, 2, 3, 4, or 5) currently inhabiting the top position
on peg 1 (left). Returns 'none' if peg is empty. Used to determine
valid responses in 'trial.choice'.
topInB: Returns the disk number (1, 2, 3, 4, or 5) currently inhabiting the top position
on peg 2 (center). Returns 'none' if peg is empty. Used to determine
valid responses in 'trial.choice'.
top_in_c Returns the disk number (1, 2, 3, 4, or 5) currently inhabiting the top position
on peg 3 (right). Returns 'none' if peg is empty. Used to determine
valid responses in 'trial.choice'.
aCount: The number of disks currently placed on peg 1 (left).
bCount: The number of disks currently placed on peg 2 (center).
cCount: The number of disks currently placed on peg 3 (right).
cumMoves: cumulative number of moves made across all test problem sets attempted
cumMovesCS: cumulative number of moves made across all test problem sets that were solved
cumOptimalMoves: cumulative number of optimal moves across those test problem sets that were attempted
cumOptimalMovesCS: cumulative number of optimal moves across those test problem sets that were solved
(2) Summary data file: 'towerofhanoi_summary*.iqdat' (a separate file for each participant)
inquisit.version: Inquisit version run
computer.platform: the platform the script was run on (win/mac/ios/android)
startDate: date script was run
startTime: time script was started
subjectId: assigned subject id number
groupId: assigned group id number
sessionId: assigned session id number
elapsedTime: time it took to run script (in ms); measured from onset to offset of script
completed: 0 = script was not completed (prematurely aborted);
1 = script was completed (all conditions run)
//Screen Setup:
(parameter) runAbsoluteSizes: true (1) = should run absolutely sized canvas (see parameters- canvasHeightMM)
false (0) = should use proportionally sized canvas (uses width = 43*screenHeight)
canvasAdjustments: NA: not applicable => parameters- runAbsoluteSize was set to 'false'
0: parameters- runAbsoluteSize was set to 'true' and screen size was large enough
1: parameters- runAbsoluteSize was set to 'true' BUT screen size was too small and
adjustments had to be made
activeCanvasHeightMM: the width of the active canvas (by default: lightGray area) in mm
activeCanvasWidthMM: the height of the active canvas in mm
display.canvasHeight: the height of the active canvas in pixels
display.canvasWidth: the width of the active canvas in pixels
pxPerMM: the conversion factor to convert pixel data into mm-results for the current monitor
(Note: the higher resolution of the current monitor
the more pixels cover the same absolute screen distance)
This factor is needed if you want to convert pixel data into absolute mm data or the other way around
runPractice (parameter): 1 = a practice session was run; 0 = otherwise
problemsStarted: lists all test problemnumbers that were started in order
problemsSolved: lists all test problemnumbers that were solved (in order)
totalScore: Score achieved across the whole set of test problems.
In this script: Max is 72
cumMoves: cumulative number of moves made across all test problem sets attempted
cumMovesCS: cumulative number of moves made across all test problem sets that were solved
cumOptimalMoves: cumulative number of optimal moves across those test problem sets that were attempted
cumOptimalMovesCS: cumulative number of optimal moves across those test problem sets that were solved
meanFirstMoveTime: mean first move time (in ms); based on all recorded first move-times
timePerMoveRatio: mean amount of time (in ms) spent on each move
(ratio of totalCompletionTime over the number of moves made)
moveAccRatio: number of moves made in relationship to the number of optimal moves
1 = participant made only the number of optimal moves (but may NOT have solved the problems)
moveAccRatioCS: number of moves made in relationship to the number of optimal moves
(only calculated for solved problems)
1 = participant made only the optimal moves for the problems solved
countViolationsTotal: counts the number of rule violations across problems
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EXPERIMENTAL SET-UP
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The default setup of the test session is based on Humes et al (1997).
However:
- you can add/edit an OPTIONAL practice session
- you can change the number of test problems run (see section Editable Lists)
- you can change the placements of the disks (see section Editable Lists),
Note that changing the disk placements will change the problems
(the maximum number of disks that can be used in this script is 5)
- you can change the goal state images under section Editable Stimuli
- you can change the scoring algorithm under expressions.scoring (see section Editable Parameters)
- you can change the number of attempts needed to move on to the next problem (see section Editable Parameters)
- you can change the number of allowed movements per attempt (see section Editable Parameters)
Note: if you change the design of the test, you may have to update your
instructions (see section Editable Instructions) accordingly
PRACTICE SETUP (OPTIONAL):
Note: the practice session is optional and can be turned on/off under section Editable Parameters.
Humes et al (1997) did not run a practice.
This script runs one practice problem: a 2-disk, 2-move tower problem
Participants are allowed 20 movements to solve the practice problem (Editable Parameter).
In this script all participants, regardless of practice performance, move on to the test.
TEST SETUP:
* 12 problems alternating tower and flat solutions, problems increase in moves from 5 to 15
(problem1-6: 3 disk problems, problem7-12: 4 disk problems)
* problems are self-paced
* each problem gets 6 attempts to solve it within 20 moves (Note: in this script, rule violations are counted as moves)
* each problem needs to be solved twice in a row to advance to the next problem.
If a problem is not solved twice in a row, the task terminates prematurely
/////Scoring////
See Humes et al (1997, p.251)
If a problem is solved successfully twice in a row within the allowable attempts,
the computer assigns the following scores:
- solved in attempts 1&2: 6 points
- solved in attempts 2&3: 5 points
- solved in attempts 3&4: 4 points
- solved in attempts 4&5: 3 points
- solved in attempts 5&6: 2 points
- else: no points
Max Range: 0-72 points
////Rule Reminders provided///
*for the first violation of each rule: a reminder of the rule is provided, and the previous set-up restored
*for subsequent violations: only a 'Violation' reminder is provided and the previous set-up restored
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STIMULI
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* provided by Millisecond Software
*see section Editable Stimuli, different base/peg/disk images can be used (in that case positions of
base/pegs/disks may have to be adjusted)
*the start and goal states of each disk can be edited under section Editable Lists)
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INSTRUCTIONS
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Instructions are provided by Millisecond Software.
They can be adjusted under section Editable Instructions.
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EDITABLE CODE
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check below for (relatively) easily editable parameters, stimuli, instructions etc.
Keep in mind that you can use this script as a template and therefore always "mess" with the entire code
to further customize your experiment.
The parameters you can change are:
