Critical thinking is a common aim for higher education students, often described as general competencies to be acquired through entire programs as well as domain-specific skills to be acquired within subjects. The aim of the study was to investigate whether statistics-specific critical thinking changed from the start of the first semester to the start of the second semester of a two-semester statistics course, where the curriculum contains learning objectives and assessment criteria related to critical thinking. The brief version of the Critical Thinking scale (CTh) from the Motivated Strategies of Learning Questionnaire addresses the core aspects of critical thinking common to three different definitions of critical thinking. Students rate item statements in relation to their statistics course using a frequency scale: 1 = never, 2 = rarely, 3 = sometimes, 4 = often, and 5 = always. Participants were two consecutive year-cohorts of full-time Bachelor of Psychology students taking a two-semester long statistics course placed in the first two semesters. Data were collected in class with a paper-pencil survey 1 month into their first semester and again 1 month into the second. The study sample consisted of 336 students (ncohort 1 = 166, ncohort 2 = 170) at baseline, the follow-up was completed by 270 students with 165 students who could be matched to their baseline response. To investigate the measurement properties of the CTh scale, item analysis by the Rasch model was conducted on baseline data and subsequently on follow-up data. Change scores at the group level were calculated as the standardized effect size (ES) (i.e., the difference between baseline and follow-up scores relative to the standard deviation of the baseline scores). Data fitted Rasch models at baseline and follow-up. The targeting of the CTh scale to the student sample was excellent at both timepoints. Absolute individual changes on the CTh ranged from −5.3 to 5.1 points, thus showing large individual changes in critical thinking. The overall standardized effect was small and negative (−0.12), with some variation in student strata defined by, gender, age, perceived adequacy of math knowledge to learn statistics, and expectation to need statistics in future employment.

Dataset for Rasch analyses of the brief Critical Thinking Scale (CTh) and assessment of change

Data from the study reported in ” Exploring first semester changes in domain-specific critical thinking”.

Data are from Danish Psychology students, and consists of three data sets containing the variables described below.

Baseline data set (n = 336)

Gender: 1 = female, 2 = male

Agegroup (median split): 1 = 21 years and younger, 2 = 22 years and older

Math (perception of own mathematical knowledge as adequate): 1 = inadequate, 2 = adequate

Statfuture (expectation to need statistics in future employment): 1 = yes, 2 = maybe, 3 = no

CTh1, CTh2, CTh5 are items of the CTh scale with response scale (item statements included in the article): 1 = never, 2 = rarely, 3 = sometimes, 4 = often, 5 = always

RescaledWML (rescaled person parameter estimates at baseline)

Matched longitunial data set dataset (n = 165)

Gender, Agegroup, Math and Statfuture were collected at baseline

Gender: 1 = female, 2 = male

Agegroup (median split): 1 = 21 years and younger, 2 = 22 years and older

Math (perception of own mathematical knowledge as adequate): 1 = inadequate, 2 = adequate

Statfuture (expectation to need statistics in future employment): 1 = yes, 2 = maybe, 3 = no

CTh1b, CTh2b, CTh5b are items of the CTh scale at baseline with response scale (item statements included in the article): 1 = never, 2 = rarely, 3 = sometimes, 4 = often, 5 = always

CTh1f, CTh2f, CTh5f are items of the CTh scale at follow-up with response scale (item statements included in the article): 1 = never, 2 = rarely, 3 = sometimes, 4 = often, 5 = always

RescaledWMLf (rescaled person parameter estimates at follow-up)

This data set contains the replication data and supplements for the article "Knowing, Doing, and Feeling: A three-year, mixed-methods study of undergraduates’ information literacy development." The survey data is from two samples: - cross-sectional sample (different students at the same point in time) - longitudinal sample (the same students and different points in time)Surveys were distributed via Qualtrics during the students' first and sixth semesters. Quantitative and qualitative data were collected and used to describe students' IL development over 3 years. Statistics from the quantitative data were analyzed in SPSS. The qualitative data was coded and analyzed thematically in NVivo. The qualitative, textual data is from semi-structured interviews with sixth-semester students in psychology at UiT, both focus groups and individual interviews. All data were collected as part of the contact author's PhD research on information literacy (IL) at UiT. The following files are included in this data set: 1. A README file which explains the quantitative data files. (2 file formats: .txt, .pdf)2. The consent form for participants (in Norwegian). (2 file formats: .txt, .pdf)3. Six data files with survey results from UiT psychology undergraduate students for the cross-sectional (n=209) and longitudinal (n=56) samples, in 3 formats (.dat, .csv, .sav). The data was collected in Qualtrics from fall 2019 to fall 2022. 4. Interview guide for 3 focus group interviews. File format: .txt5. Interview guides for 7 individual interviews - first round (n=4) and second round (n=3). File format: .txt 6. The 21-item IL test (Tromsø Information Literacy Test = TILT), in English and Norwegian. TILT is used for assessing students' knowledge of three aspects of IL: evaluating sources, using sources, and seeking information. The test is multiple choice, with four alternative answers for each item. This test is a "KNOW-measure," intended to measure what students know about information literacy. (2 file formats: .txt, .pdf)7. Survey questions related to interest - specifically students' interest in being or becoming information literate - in 3 parts (all in English and Norwegian): a) information and questions about the 4 phases of interest; b) interest questionnaire with 26 items in 7 subscales (Tromsø Interest Questionnaire - TRIQ); c) Survey questions about IL and interest, need, and intent. (2 file formats: .txt, .pdf)8. Information about the assignment-based measures used to measure what students do in practice when evaluating and using sources. Students were evaluated with these measures in their first and sixth semesters. (2 file formats: .txt, .pdf)9. The Norwegain Centre for Research Data's (NSD) 2019 assessment of the notification form for personal data for the PhD research project. In Norwegian. (Format: .pdf)

This study is a cross-sectional, hospital-based observational study conducted from July 2019 to March 2020 at Kasturba Hospital of Kasturba Medical College, Manipal, a tertiary care centre in Udupi district of Karnataka state in India. The sample consisted of medical practitioners working in various clinical branches of medicine of Kasturba Hospital, Manipal, with a minimum of one year of experience. Convenience sampling was used. Written informed consent was obtained from all participants. The sample size was calculated using the formula for statistically significant correlation coefficient and it was calculated as185. Participants’ age, gender and work experience details were documented in a proforma. Psychological flexibility was measured using Acceptance and action questionnaire-II (AAQ-II; Bond et al, 2011). Professional Quality of Life Scale Version 5 (ProQol 5; Stamm, 2010) was used to measure compassion satisfaction (CS), burnout (BO) and secondary traumatic stress (STS) among participants. The collected data was analyzed using IBM Statistical Package for Social Sciences (SPSS) statistics for Windows, Version 25 (IBM Corp, Armonk, NY, USA). Descriptive statistics were used to summarize the data. Mean and standard deviation (SD) were used for continuous data. Group differences across gender for continuous variables were examined using an independent t-test and P values less than 0.05 were considered significant. To establish the relationship between the variables Pearson’s’ correlation test was used.

The research hypothesis stated was that there would be no relationship between psychological flexibility and 1) compassion satisfaction, 2) burnout and 3) secondary traumatic stress among medical practitioners.

Out of the 185 that could complete the study, it included 70 females and 115 males. Mean age of the sample was 37.31 years. In terms of years of work experience, 149 doctors had less than 20 years of experience and 36 had more than 20 years of experience.

Mean scores of acceptance and action questionnaire-II and professional quality of life scale version 5 were analysed. Compassion Satisfaction had a mean score of 35.89, Burnout has a mean score of 24.97, Secondary Traumatic Stress had a mean score of 20.43 and Psychological Inflexibility had a mean score of 15.69.

The result of Pearson’s correlation showed the relationship between compassion satisfaction and psychological inflexibility was not significantly correlated. The relationship between burnout and psychological inflexibility is significantly and strongly positively correlated. The relationship between secondary traumatic stress and psychological inflexibility is significantly and strongly positively correlated. Using a t-test, it was shown that compassion satisfaction was relatively higher for females and burnout was relatively higher in males.

Welcome to third season of Bold Signals!In this episode:1. Scenes from the Replication Crisis: Ronald Fisher and the P-Value. [0:01:00]2. An extended interview with Brian Nosek, Social Psychologist and Director of the Center for Open Science. [0:09:25]3. Bold Signals Documentary Club: Cosmos: A Personal Journey (Episode 1). [0:56:58]Music in this Episode:"Enterprise 1" by Languis"Trees Don't Sleep" by Zachary Cale, Mighty Moon & Ethan Schmid"Shoegaze" by Jahzzar"Lights Over Tomorrow" by Starover Blue"Not a Song" by Scrapple"Cabalista" by Wild FlagCover Art: "Homebrew" by Robert Tinney

The study was conducted to evaluate the psychological effects of long-term administrative segregation (AS) on offenders, particularly those with mental illness. The longitudinal study examined five groups of inmates in the Colorado prison system over the course of one year: inmates in AS at the Colorado State Penitentiary (CSP) with mental illness, inmates in AS at the CSP without mental illness, inmates at risk of AS in the general population (GP) with mental illness, inmates at risk of AS in the GP without mental illness, and inmates at the San Carlos Correctional Facility, a facility for offenders with severe mental illness. Over the course of the study, researchers assessed each group of inmates using 14 psychological instruments, most of which were administered at three month intervals. Of the 14 psychological instruments, 12 were self-reports by inmates, 1 was filled out by mental health clinicians, and 1 was filled out by correctional staff.

IVs are Orientation (Upright, Inverted), Target Name (Friend, Self, Unfamiliar) and Distractor Face (Friend, Self, Unfamiliar). All IVs are repeated-measures. The DV is reaction time (RT) for correct responses, measured in ms. Incorrect responses accounted for 5.2% of the data, and were removed prior to analysis (i.e. data presented here are for correct responses). For each participant, RT’s more than two standard deviations away from that participant’s mean were removed as outliers; these accounted for 10.3% of trials. Data presented here do not include these trials. Variables are labelled as follows: Orientation I = Inverted Up = Upright Target Name F = Friend S = Self U = Unfamiliar Distractor Face F = Friend S = Self U = Unfamiliar For example, the variable labelled “ISF” contains the average reaction time to respond a name when the Distractor Face was presented in an Inverted Orientation, when the Target Name to respond to was the participant’s own name, and when the Distractor Face was an image of a Friend.

The distribution of effect sizes may offer insights about the research done and reported in a scientific field. We have evaluated 12,412 manually collected correlation effect sizes (Sample 1) and 31,157 computer-extracted correlation effect sizes (Sample 2) published in journals focused on social or developmental psychology. Sample 1 consisted of 243 studies from 6 journals published in 2010 and 2019. Sample 2 consisted of 5,012 papers published in 10 journals between 2010–2019. The 25th, 50th and 75th effect size percentiles were 0.08, 0.17 and 0.33, and 0.17, 0.31, and 0.52 in Samples 1 and 2, respectively. Sample 2 percentiles were probably larger because Sample 2 only included effect sizes from the text but not from tables. In text, authors may have emphasized larger correlations. Large sample sizes were associated with smaller reported correlations. In Sample 1 about 70% of studies specified a directional hypothesis. In 2010, no papers had power calculations while in 2019, 14% of p...

This study was conducted to examine the psychological reactions experienced by families of missing children and to evaluate families' utilization of and satisfaction with intervention services. To address issues of psychological consequences, the events occurring prior to child loss, during the experience of child loss, and after child recovery (if applicable) were studied from multiple perspectives within the family by interviewing parents, spouses, siblings, and, when possible, the missing child. A sample of 249 families with one or more missing children were followed with in-home interviews, in a time series measurement design. Three time periods were used: Time Series 1, within 45 days of disappearance, Time Series 2, at 4 months post-disappearance, and Time Series 3, at 8 months post-disappearance. Three groups of missing children and their families were studied: loss from alleged nonfamily abduction (stranger), loss by alleged family or parental abduction, and loss by alleged runaway. Cases were selected from four confidential sites in the United States. The files in this collection consist of data from detailed structured interviews (Parts 1-22) and selected quantitative nationally-normed measurement instruments (Parts 23-33). Structured interview items covered: (1) family of origin for parents of the missing child or children, (2) demographics of the current family with the missing child or children, (3) conditions in the family before the child's disappearance, (4) circumstances of the child's disappearance, (5) perception of the child's disappearance, (6) missing child search, (7) nonmissing child, concurrent family stress, (8) coping with the child's disappearance, (9) coping with a nonmissing child, concurrent family stress, (10) missing child recovery, if applicable, (11) recovered child reunification with family, if applicable, and (12) resource and assistance evaluation. With respect to intervention services, utilization of and satisfaction with these services were assessed in each of the following categories: law enforcement services, mental health services, missing child center services, within-family social support, and community social support. The quantitative instruments collected data on family members' stress levels and reactions to stress, using the Symptom Check List-90, Achenbach Child Behavior Check List, Family Inventory of Life Events, F-COPES, Frederick Trauma Reaction Index-Adult, and Frederick Trauma Reaction Index-Child.

This dataset comprises scores of 8,954 first-year psychology students from the University of Amsterdam (1982-2007) on the ‘Vijf PersoonlijkheidsFactoren Test’ or 5PFT (Elshout & Akkerman, 1975), which is an instrument to measure the Big Five personality factors Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness to Experience. Selection of participants as described in Smits et al. on page 1126 and in their Table 1.This dataset formed the basis of the article "Cohort Differences in Big Five Personality Factors Over a Period of 25 Years" (See the link to the DOI in the Relationfield) authored by Iris A. M. Smits, Conor V. Dolan, Harrie C.M. Vorst, Jelte M. Wicherts, & Marieke E. Timmerman.A data paper about this data is available at: Smits, Iris A. M., Dolan, C. V., Vorst, H. C. M., Wicherts, J M., Timmerman, M. E. Data from ‘Cohort Differences in Big Five Personality Factors Over a Period of 25 Years’. Journal of Open Psychology Data 1(1). (See the link to the DOI in the Relationfield)This data is released under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Data are available both in CSV format (with a txt codebook) and as a SPSS .sav file.

This dataset consists of 1163 responses and 14 columns (features), focusing on the relationship between smoking, alcohol consumption, and psychological wellness among university students. It includes self-reported data on smoking and drinking habits, coping mechanisms, mental health, and help-seeking behaviors. The survey was designed to capture insights into how these behaviors impact students' overall well-being.

Data Collection: The data was collected through an online survey administered via Google Forms in [month/year]. Respondents provided information about their lifestyle habits, reasons for engaging in these behaviors, and their psychological wellness.

Key Features: 1. Demographics: Age, year of study, and field of study. 2. Smoking Habits: Frequency of smoking, age of starting, and reasons for smoking. 3. Alcohol Consumption: Frequency of alcohol use, typical weekly intake, and reasons for drinking. 4. Stress Management: Methods for coping with stress, including smoking and alcohol. 5. Mental Health: Self-reported psychological wellness and willingness to reduce or quit smoking and drinking. 6. Help-Seeking Behavior: Responses regarding help-seeking for mental health concerns.

This dataset can be used for: 1. Machine learning analysis to model and predict psychological wellness based on lifestyle behaviors. 2. Statistical studies on the interplay between smoking, alcohol, and mental health. 3. Development of intervention strategies to improve student well-being and reduce harmful habits.

Format: The dataset contains 14 columns with categorical, ordinal, and numerical data. It is formatted for ease of analysis and ready for use in statistical and machine learning applications.

Gateway courses are foundational prerequisite courses that undergraduate students must complete prior to enrolling in major courses (e.g., first-year mathematics, chemistry, psychology, statistics). Gateway courses often have high enrolment, and provide less support, structure, and feedback compared to previous experiences (e.g., secondary school). Declines in students' motivation and performance are common. This PhD project investigated two sources of engagement and motivation: self-efficacy and interest across two mathematics gateway courses. In particular, factors related to how self-efficacy and interest changed during the courses were examined across the studies. Four studies were conducted across five offerings of these two courses from 2020-2022. Participants were students enrolled in these courses. Study 1 (n=175; Sept-Dec 2020; Course 1) was conducted in an online (pandemic) setting. The interplay between students' (amounts of) self-efficacy, interest, and performances (i.e., quizzes) across the course was investigated. Study 2 (n=349; Sept-Dec 2021; Course 1) was conducted the next year, and examined how overall self-efficacy changes, and how those changes were associated with performances across a course, and interest at the end of the course. Study 3 (n=313; Sept-Dec 2021; Course 2) investigated short-term changes in interest, and how they were related to performance, and self-efficacy. Lastly, Study 4 contained two studies (n=299; n=407; Studies 4a, 4b; Courses 1 & 2) that investigated the interplay between perceived difficulty on performance tasks (i.e., quizzes), short-term changes in self-efficacy, performances, and interest (in the second study).The data files are the datasets used to conduct the analyses across the four studies. These included students' responses on formative quizzes, and self-reported data on self-efficacy, interest, perceived difficulty, and gender. These data were used for quantitative analysis using MPlus and other software. Each folder contains the relevant files each study (presented in the respective chapter of the thesis).1) Chapter 3 - Study 1 contains the dataset used for the first study. This study is already published.2) Chapter 4 - Study 2 contains the datasets used for the second study, including for the full model, invariance and reliability testing, and dataset for IRT.3) Chapter 5 - Study 3 contains the datasets used for the third study, including for the full model and dataset for IRT.4) Chapter 6 - Study 4 (Studies 4a and 4b) contains the datasets used for the last study, including those used for the full model, dataset for IRT, and perceived difficulty.

Abstract copyright UK Data Service and data collection copyright owner.

The purpose of this study was to investigate the degree of stability and change in abilities and personality in individuals and sub-groups. To examine the effects of sex and social class differences on development trends of these cognitive abilities and personality growth.
(Questionnaires were also administered when children were aged 7 and 8, but these data are not currently deposited in the Archive.)

Main Topics:

Attitudinal/Behavioural Questions
Aged five (interview with mother)
Effects on the child and his/her general behaviour in the following circumstances: change in the family; away with family; child-minded; school. Health of mother, difficulties with child - feeding, sleeping, toilet training. Child: habits; fears; play; emotional characteristics; independence; interest/response to e.g. nakedness, God, death.
Background Variables
Age, sex, health, school.

This data collection was designed to examine the effectiveness of a New York City agency's attempt to decrease the negative emotions that result from victimization. The data address the following questions: (1) To what extent do specific treatments mitigate the negative psychological impact of victimization? (2) Are individuals from a particular demographic group more prone to suffer from psychological adjustment problems following victimization? (3) When victimized, do individuals blame themselves or the situation? (4) Are some crimes more difficult to cope with than others? (5) Does previous victimization affect the likelihood that an individual will have difficulty coping with current as well as future victimization? Data were collected in two waves, with Wave 1 interviews completed within one month of the victimization incident and Wave 2 interviews completed three months after treatment. The effects of three treatments were measured. They included: traditional crisis counseling (which incorporates psychological aid and material assistance such as food, shelter, cash, etc.), cognitive restructuring (challenges to "irrational" beliefs about the world and one's self used in conjunction with crisis counseling), and material assistance only (no psychological aid provided). A fourth group of victims received no treatment or services. Three standardized psychometric scales were used in the study. In addition to these standardized scales, the initial assessment battery included an index of fear of crime as well as an index that measured behavior adjustment. Another set of measures assessed how victims perceived their experience of victimization and included items on self-blame, selective evaluation, and control. Also included were questions about the crime and precautions taken to guard against future victimization. The follow-up assessment battery was virtually identical to the initial battery, except that questions about services and social support received by the victim were added. The following demographic variables are included in the data: sex, age, marital status, education, income, and race. The unit of analysis was the individual.

This data collection contains data from the first of four studies conducted on the associated ESRC grant (data from the other studies will be made available as separate datasets in ReShare). The purpose of this study was to investigate the extent to which primary memory development constrains the development of working memory in children, and whether primary memory capacity mediates the relationship between working memory and academic attainment. To that end, a sample of 101 children aged between 5 and 8 years were given three novel experimental measures of primary memory capacity that were designed to estimate the number of items in a child's immediate memory that they could spontaneously recalled in correct serial order. More traditional experimental measures of short-term and working-memory capacity were also administered, as were standardised tests of reading [Sentence Completion Forms of the NFER-Nelson (1998) Group Reading Test II Form A (6–14)] and mathematics [NFER-Nelson (1994) Mathematics 6–14]. These data underpin the following paper: Hall, D., Jarrold, C., Towse, John N., & Zarandi, A. L. (2015). The developmental influence of primary memory capacity on working memory and academic achievement. Developmental Psychology, 51, 1131-1147. doi: 10.1037/a0039464 which is available as an open access publication (see related resources section). The data are also available via the University of Bristol data repository (see related resources section).

Dataset

This dataset was created by Zaber Ibn Abdul Hakim

Contents

This dataset contains data from 30 participants who completed the same questionnaire on meat consumption 12 times. The participant’s opinion was perturbed on each of the 11 items and measured to what extent this changed the participant’s scores on the questionnaire. It is a unique dataset that can be used for several purposes. The questionnaire data can aid research that aims to infer causal relations between variables.

Task: The dataset can be used to study causal discovery.

Summary:

• Size of dataset: 360 x 11
• Task: Causal Discovery
• Data Type: Discrete
• Dataset Scope: Standalone
• Ground Truth: Known
• Temporal Structure: Static
• License: TBD
• Missing Values: No

Missingness Statement: There are no missing values.

Features: Each measurement is a a six-level factor with levels 1 (completely disagree) to 6 (completely agree)

• moral: Eating meat is morally wrong
• nutr: Meat contains important nutrients for your body
• envir: The production of meat if harmful for the environment
• infer: Animals are inferior to people
• suff: By consuming meat you contribute to animal suffering
• tax: There should be a tax on meat
• taste: I like the taste of meat
• death: Meat reminds me of death and suffering of animals
• sad: If I had to stop eating meat I would feel sad
• guilty: If I eat meat I feel guilty
• disg: If I eat meat I feel disgust

The "Ground Truth" was obtained by the conditional invariant prediction method applied to the data on attitudes of meat consumption.

The data were obtained through an experience sampling method (ESM) survey of 71 adults (33 males and 38 females, ages 21-67) living in Japan. Exkuma software (https://exkuma.com) was used to record the response timing and collect the response data. A pre-survey was conducted on the first day of the survey (Day 1). Respondents reported their gender, age, household income, and subjective economic status. Individual differences in gain-approach/loss-avoidance orientations were measured using 14 items from the Japanese version of the Promotion/Prevention Focus Scale (PPFS-J; Ozaki & Karasawa, 2011). From the second day of the survey, a 7-day ESM survey was conducted (Days 2-8). As a survey procedure, four signals were sent to participants' smartphones each day at random times between 9:00 a.m. and 9:00 p.m. to prompt them to respond to an online survey. Participants rated their emotional state at the time of response using a 7-point scale, and then reported on their recent economic behaviors (consumption or saving) within the hour prior to the beginning of the response. The variables comprising the data are as follows: SignalDate (Date and time of signal transmission), SignalSeconds (Time from transmission to responding in seconds), SignalOrder (Signal order, range: 1-28), StartDate (Start date and time of response), FinishDate (Finish date and time of response), SurveySeconds (Duration of response in seconds), id (ID number of participants), e_prom_pos (Rating of promotion-related positive emotion “cheerful”, range: 1-7), e_prev_pos (Rating of prevention-related positive emotion “calm”, range: 1-7), e_prom_neg (Rating of promotion-related negative emotion “dejected”, range: 1-7), e_prev_neg (Rating of prevention-related negative emotion “agitated”, range: 1-7), done_c (Recent consumption behavior; yes = 1, no = 0), done_s (Recent saving behavior; yes = 1, no = 0), age (Age), gender (Gender; male = 1, female = -1, no response = 0), income (Annual income in millions of yen; No response = .), economic_s (Subjective economic status, range: 1-7), prom_scale (Gain-approach orientation, range: 1-7), prev_scale (Loss-aversion orientation, range: 1-7), age_m_c (Age [grand-mean centered]), income_m_c (Income [grand-mean centered]; No response was converted to “0”), prom_m_c (Gain-approach orientation [grand-mean centered]). prev_m_c (Loss-aversion orientation [grand-mean centered]), economic_m_c (Subjective economic status [grand-mean centered]).

Autism Spectrum Disorder (ASD) has generated much research interest in recent times due to a soaring increase in diagnosis rates and a movement to recognise ASD as a cognitive style, rather than a cognitive deficit. Psychologists are responsible for the timely and accurate diagnosis of ASD and supporting clients on the spectrum with general mental health care. Undergraduate psychology students may go on to further study to become registered psychologists or choose to pursue other careers in mental health care and support work in which they will likely have contact with members of the autistic community. However, little research into the attitudes towards and knowledge of autism in psychology students in Australia has been conducted. In this exploratory study, 1st year (n=23) and 3rd year (n=64) undergraduate psychology students were surveyed, and the results compared to see if a significant difference exists between cohorts. That is, to ascertain if attitudes towards and knowledge of autism improved in students studying an undergraduate psychology major. Results indicated that there was no significant difference in knowledge and attitudes towards autism between the 1st and 3rd year student cohorts. Implications for psychology students, universities, the autistic population, and the future direction of research in this area are discussed.