DOI: 10.5061/dryad.ht76hdrtk
title: Data from: Constructing concepts without feedback: An empirical investigation of how relational information affects multidimensional concept completion behavior in an unsupervised task

description: The ability of humans to intentionally learn, without feedback,
 unidimensional stimulus relations in categorization tasks has been
 empirically established over the past two decades.  However,
 whether observers can learn more complex multidimensional stimulus
 relations across these unsupervised tasks has not yet been
 determined.  We demonstrate across an unsupervised concept
 completion experiment that the failure to observe multidimensional
 learning in previous experiments may be attributable to factors such as
 increased stimulus or task complexity.  We posit that concept
 completion is related to category learning in that it reveals the
 underlying tendencies that are associated with some categories being
 easier to learn than others.  In our experiments, we found
 observers readily learned to complete a two-dimensional exclusive-or
 concept, evidenced by an increase in object selection as the task
 progressed with a decrease in choice response times. We also found that
 observers readily learned to complete, as evidenced by similar patterns in
 object selection and response time behavior, a more complex
 three-dimensional stimulus relation that has empirically been associated
 with large amounts of categorization errors in related supervised
 classification tasks.  Accordingly, we tested two existing formal
 models to determine their ability to account for our observations: namely,
 the Simplicity Model and the Generalized Representational Information
 Theory (GRIT) basic measure. We show how relational information processing
 as expounded in GRIT accounts for the observed completion
 behavior.  Overall, our findings show how people gravitate, in a
 gradual and composite fashion, towards minimizing the perceived complexity
 of categories as much as possible. 
description: # Data from: Constructing concepts without feedback: An empirical
 investigation of how relational information affects multidimensional
 concept completion behavior in an unsupervised task Dataset DOI:
 [10.5061/dryad.ht76hdrtk](10.5061/dryad.ht76hdrtk) ## Description of the
 data and file structure This dataset contains the raw and processed data
 for the pilot experiment and the main experiment reported in Doan and Vigo
 (In Press, PLOS One), for assessing whether individuals display an
 increase in multidimensional concept completion behavior across trials of
 the concept completion task used by the authors.  Data cover six
 repeated-measures conditions of concept completions for the pilot
 experiment (1D-XOR-C3D, 1D-C3D-XOR, XOR-1D-C3D, XOR-C3D-1D, C3D-1D-XOR,
 C3D-XOR-1D) and two between-subjects conditions of concept completions for
 the main experiment (XOR-XOR, C3D-C3D).  For each experiment, we include
 data associated with the series of objects seen by participants (partial
 1D, XOR, or C3D concept) and the set of five objects from which they
 selected to complete the partial concept.  For each trial of each
 experiment, we include data on which object from the set of five objects
 was selected by each participant and the accompanying response time to
 make the selection.  Statistical analyses on the processed pilot data
 revealed statistical increases in XOR and C3D concept completions and
 statistical decreases in response times to make these decisions for
 participants' first task in the pilot experiment.  The main
 experiment sought to replicate and extend these results with substantially
 more statistical power.  Regression analyses on the processed data for the
 main experiment revealed statistically-significant increases in XOR and
 C3D concept completions and statistically-significant decreases in
 response times to make these decisions.  The results indicated a
 logarithmic increase in XOR completion behavior from task 1 to task 2 and
 a linear increase in C3D completion behavior from task 1 to task 2.  The
 results indicated logarithmic statistically-significant decreases in
 response times to make completion decisions across tasks 1 and 2 for both
 the XOR and C3D concepts. ### Files and variables #### File:
 GRIT_NPE_ModelPredictions.xlsx **Description:** This file contains formal
 model predictions from Generalized Representational Information Theory for
 the three concept completion conditions (1D, XOR, C3D).  Formulas
 associated with calculating the model predictions provided in column S are
 provided in cells M and O-S.  ##### Variables * Fam = Describes the
 dimensional makeup of the categorical stimulus along with the number of
 positive examples of the category (3[3] = 3 dimensions and 3 positive
 examples). * Type = Logical configuration of the positive examples (binary
 dimensions = Boolean). Type 1 = 1D partial, Type 2 = XOR partial, Type 3 =
 C3D partial. * Objects = Binary notation of the object stimuli belonging
 to the categorical stimulus (3 object stimuli/positive examples) or that
 were the resulting categorical stimulus after one of the other five object
 stimuli were added (completion decision; 4 object stimuli). * Logical
 Manifold = Degree of dimensional diagnosticity for each of the stimulus
 dimensions (each is a structural kernel) as determined via the
 invariance-detection process as described in Generalized Invariance
 Structure Theory (GIST; Vigo, 2013, 2015).  * D = Number of stimulus
 dimensions composing the object stimuli. * P = Number of object stimuli as
 positive examples of the categorical stimulus. * D1-D3 = Numerator of the
 each logical manifold structural kernel.  * Alpha1-Alpha3 = Sensitivity
 parameters (not estimated or used for the current study). * k = Scaling
 parameter reflecting degree of discriminability between different
 categorical stimuli for observers (nonparametric value = 2/D; not
 estimated for the current study). * Disc. Param = Metric selection. The
 value is 1 if City-block metric (Integral dimension stimuli; Vigo, Doan,
 & Zhao, 2022) and the value is 2 if Euclidean metric (Separable
 dimension stimuli; Vigo, Doan, & Zhao, 2022). * Phi = Degree of
 categorical invariance of the categorical stimulus as calculated using
 GIST (Vigo, 2013, 2015).  * Phi^2 = The squared value of the degree of
 categorical invariance of the categorical stimulus as calculated using
 GIST (Vigo, 2013, 2015).  * Lambda = Degree of structural equilibrium of
 the categorical stimulus as calculated using GIST (Vigo, 2013, 2015). *
 GISTM-NPE (Lambda) = The non-parametric Generalized Invariance Structure
 Theory Model using the Lambda variant for structural equilibrium. *
 GRIT-NPE (Lambda) = The non-parametric Generalized Representational
 Information Theory Model using the Lambda variant for structural
 equilibrium.  This model is a rate of change measure in conceptual
 complexity.  For the current task, the model predicts observers will
 select the object to add to the 3-object category (partial concept) that
 minimizes the complexity of the resulting category (the bolded values; see
 Doan & Vigo, 2016, 2023, in press for more information).  #### File:
 Main_Experiment_XOR_C3D_Data.xlsx **Description:** This file contains the
 raw and processed concept completion data (selections, response times) for
 the main experiment reported in Doan and Vigo (In Press, PLOS One).  There
 are two sheets in the Excel file that represent the raw data: MainExpt_XOR
 (raw data), MainExpt_C3D (raw data).  The cells that are highlighted red
 in these two sheets represent participant(s) who were excluded from the
 main analyses in the paper due to not selecting the XOR or C3D relation
 most often.  The cells that are highlighted yellow in these two sheets
 represent participant(s) who did not select the XOR or C3D relation most
 often for at least one of the two tasks, but who did overall have more XOR
 or C3D selections compared to alternative possibilities. The bolded values
 in these sheets represent the relation that was selected most frequently
 for each participant and task. There are three sheets in the Excel file
 that represent the processed data: Data Set_Prop (Maj), Data Set_RT_2SD
 (Maj), Data Set_RT (Maj). The bolded red values in the rightmost sheet
 (Data Set_RT (Maj)) represent averages response times that were more than
 two standard deviations above the mean for that block of trials and were
 thus excluded from the main analyses (Outliers; see sheet Set_RT_2SD
 (Maj)). In cells located in rows 52-54, we provide the Excel formulas for
 calculating the mean RT, the standard deviation of the RT, and the two
 standard deviation upper limit used for determining the bolded red values
 (Outliers). ##### Variables * PN = Anonymized Participant Number * Task
 = First or second task for the participant (1, 2) * Stimuli = Type of
 stimulus shown for that Task number for that participant (Clock, Tshirt) *
 TrialNumber = As labeled (one series of 3 clocks + modification decision
 of 5 clocks thereafter) * Type = Boolean structure type (2 = 3[3] - II =
 XOR; 3 = 3[3] - III = C-3D) * Instance = The specific instance of the
 Boolean structure type (3 objects presented in the series) * Inst_align_t#
 = The particular object belonging to the Boolean structure type instance
 (see above; limited to 3 columns). "Align" refers to fact that
 entire column of objects occupy the same structural role. * Inst_align_b#
 = The particular object possible to add to the Boolean structure type
 instance (limited to 5 columns for the 5 objects possible to add on each
 trial). "Align" refers to fact that entire column of objects
 occupy the same structural role. * Inst_shuff_t# = A randomized order of
 the three objects belonging to the Boolean structure type instance (e.g.,
 compare "Inst_align_t#" to these columns). * Inst_shuff_b# = The
 randomized order of the five objects possible to add to the Boolean
 structure type instance (e.g., compare "Inst_align_b#" to these
 columns). This was the order shown left to right to participants. *
 Inst_shuff_t#_o# = The randomized order of the three objects belonging to
 the Boolean structure type instance (e.g., compare
 "Inst_align_t#" to these columns). Shown to participants in this
 order (left to right on screen). * StartTime = The internal timestamp
 clocked by the computer at the start of the Trial. * RTime = The amount of
 time passed from onset of Trial (StartTime) and when the mouse clicked on
 one of the 5 objects enclosed in the white box (The program only advanced
 if mouse clicked on one of the five objects). * Choice = The object
 selected by the participant out of the 5 objects enclosed in the white box
 (e.g., compare this object to the objects in the "Inst_align_b#"
 columns). * xCoord = The horizontal pixel location of the mouse click on
 the computer screen. * yCoord = The vertical pixel location of the mouse
 click on the computer screen. * Choice_Obj = Excel function determining
 whether the chosen object (Choice) refers to the aligned bottom object 1,
 2, 3, 4, or 5 (see "Inst_align_b#). * PropCorr_#_XOR = Proportion of
 completion decisions consistent with selecting the XOR object from the set
 of 5 for that block of 4 trials (PropCorr_4_XOR = trials 1-4,
 PropCorr_8_XOR = trials 5-8, etc.). * PropCorr_#_C3D = Proportion of
 completion decisions consistent with selecting the C-3D object from the
 set of 5 for that block of 4 trials (PropCorr_4_C-3D = trials 1-4,
 PropCorr_8_C-3D = trials 5-8, etc.). * RT_#_XOR = Average response time
 for making a decision from the set of 5 for that block of 4 trials
 (RT_4_XOR = trials 1-4, RT_8_XOR = trials 5-8, etc.). * RT_#_C3D = Average
 response time for making a decision from the set of 5 for that block of 4
 trials (RT_4_C3D = trials 1-4, RT_8_C3D = trials 5-8, etc.). #### File:
 Pilot_Experiment_1D_XOR_C3D_Data.xlsx **Description:** This file contains
 the raw and processed concept completion data (selections, response times)
 for the pilot experiment reported in Doan and Vigo (In Press, PLOS One). 
 There are three sheets in the Excel file that contain the raw data:
 Type_3_3_1 (raw_data), Type_3_3_2 (raw_data), Type_3_3_3 (raw_data).  The
 bolded values in these sheets represent the relation that was selected
 most frequently for each participant and task. There are two sheets in the
 Excel file that contain the processed data in full: Full Data Set_Prop,
 Full Data Set_RT. There are two sheets in the Excel file that contain the
 processed data after removing participants who did not predominantly
 engage in 1D, XOR, or C3D concept completion behavior: Data
 Set_1D_XOR_C3D_Prop, Data Set_1D_XOR_C3D_RT. ##### Variables * PN =
 Anonymized Participant Number * TrialNumber = As labeled (one series of 3
 clocks + modification decision of 5 clocks thereafter) * Type = Boolean
 structure type (1 = 3[3] = 1D; 2 = 3[3] - II = XOR; 3 = 3[3] - III = C-3D)
 * Instance = The specific instance of the Boolean structure type (3
 objects presented in the series) * Inst_align_t# = The particular object
 belonging to the Boolean structure type instance (see above; limited to 3
 columns). "Align" refers to fact that entire column of objects
 occupy the same structural role. * Inst_align_b# = The particular object
 possible to add to the Boolean structure type instance (limited to 5
 columns for the 5 objects possible to add on each trial).
 "Align" refers to fact that entire column of objects occupy the
 same structural role. * Inst_shuff_t# = A randomized order of the three
 objects belonging to the Boolean structure type instance (e.g., compare
 "Inst_align_t#" to these columns). * Inst_shuff_b# = The
 randomized order of the five objects possible to add to the Boolean
 structure type instance (e.g., compare "Inst_align_b#" to these
 columns). This was the order shown left to right to participants. *
 Inst_shuff_t#_o# = The randomized order of the three objects belonging to
 the Boolean structure type instance (e.g., compare
 "Inst_align_t#" to these columns). Shown to participants in this
 order (left to right on screen). * StartTime = The internal timestamp
 clocked by the computer at the start of the Trial. * RTime = The amount of
 time passed from onset of Trial (StartTime) and when the mouse clicked on
 one of the 5 objects enclosed in the white box (The program only advanced
 if mouse clicked on one of the five objects). * Choice = The object
 selected by the participant out of the 5 objects enclosed in the white box
 (e.g., compare this object to the objects in the "Inst_align_b#"
 columns). * xCoord = The horizontal pixel location of the mouse click on
 the computer screen. * yCoord = The vertical pixel location of the mouse
 click on the computer screen. * Choice_Obj = Excel function determining
 whether the chosen object (Choice) refers to the aligned bottom object 1,
 2, 3, 4, or 5 (see "Inst_align_b#). * Order = The value for the
 between-subjects variable of presentation order. (1 = 1D, XOR, C3D; 2 =
 1D, C3D, XOR; 3 = XOR, 1D, C3D; 4 = XOR, C3D, 1D; 5 = C3D, 1D, XOR; 6 =
 C3D, XOR, 1D). * 1st_Task = The specific strategy associated with the
 first task for that participant (1D = Order 1 or 2; XOR = Order 3 or 4;
 C3D = Order 5 or 6). * 1D_Block# = Proportion of completion decisions
 consistent with 1D sorting strategy across the four trials in this block.
 * XOR_Block# = Proportion of completion decisions consistent with XOR
 sorting strategy across the four trials in this block. * C3D_Block#
 = Proportion of completion decisions consistent with C3D sorting strategy
 across the four trials in this block. ## Code/software JASP version 0.19.3
 was used for statistical analyses and can be used to view the data.  ##
 Human subjects data Participants provided written and verbal informed
 consent. Each participant was assigned a unique number, which was neither
 attached to nor stored with their name. There is no existing document that
 links the number with any participant's name, making it impossible to
 determine whose data belongs to any participant.