Instructions Need this work in 1500 words | single spaced Level of writing - Sophomore Refer to attached guide and sample for detail. data is attached. Referencing style is APA, make sure you meet all the requirements of apa. use the template to write the hypothesis and the report. example is attached. use the required references in the guide as main but 8-12 references in total should be used. make sure you check with the rubric to ensure you are meeting the requirements/n Abi Brooker PhD The University of Melbourne Lab report marking guide Developmental Psychology (PSYC20008) Overview The aim of this lab report is to learn about lifespan developmental psychology, by investigating associations between university students' language use (linguality) and their cognitive, biological, social, or emotional developmental experiences. Students will also learn to conduct, interpret, and report chi-square tests of independence. They will complete two chi-square analyses: (i) Analysis 1 addresses a hypothesis provided by the teaching team; (ii) i February, 2024 This assignment is worth 40% of the total mark for Developmental Psychology (PSYC20008). Due 8:00 AM, Tuesday 30 April 2024. Analysis 2 addresses a second hypothesis created by the student depending on their own interests. Word limit The 1500-word limit includes the Abstract, Introduction, Results, Discussion, and in-text citations. The 10% word-limit penalty applies as per the Student Manual. The following items are not included word limit but are expected: • The Method. Students can write their own Method or use the Method that they develop with their class in Lab 2. Other report elements. Headings, sub-headings, tables, title page, keywords (under the Abstract) and a reference list. Hypotheses The report will have two hypotheses. Each hypothesis has two sentences. The first sentence includes information about who the prediction refers to (e.g., the full sample, or a smaller group within the sample), and identifies the two variables being used in the analysis. The second sentence makes a prediction about what the relationship between the variables will look like, with reference to one category in each variable. A templated example of a hypothesis that leads to a chi-square analysis is below. You can (and should!) use this template when writing out your hypotheses: Among [sample / specific group within sample], there will be a statistically significant relationship between [one categorical variable] and [another categorical variable]. More/fewer participants with [a specific category in the first variable] will report [a specific category in the second variable] than expected by chance. Hypothesis 1: All students will have the same first hypothesis (with some variation, as noted below). The first hypothesis explores the relationship between two categorical variables: (i) linguality (monolingual, bilingual, multilingual), and (ii) cognitive control (higher, medium, lower). More information about these variables can be found on Page 2. • Among PSYC20008 students who answered an N-back trial question correctly, there will be a statistically significant association between language use and cognitive control. [Follow this with one sentence predicting what the relationship will look like. Some examples are below.] More/Fewer participants will have cognitive control than expected by chance. • More multilingual participants will have higher cognitive control than expected by chance. • Fewer monolingual participants will have lower cognitive control than expected by chance. Hypothesis 2: Students will create their second hypothesis, and run their second chi-square hypothesis, on their own. We recommend (not mandatory) that students change one or two blue elements from the first hypothesis and keep one element consistent across both hypotheses (e.g., both hypotheses focus on the same specific group, or linguality, or cognitive control). This will help ensure that their report is cohesive and consistent. Participants We invite PSYC20008 students during Semester 1 to complete the survey for this learning activity. At the time of writing this Lab Report Guide, there are approximately 1,110 students enrolled in PSYC20008. Just over half of the cohort (52%) are enrolled in a Bachelor of Arts, with smaller proportions enrolled in Science (31%), Graduate Diploma in Psychology (11%), Biomedicine (4%), and other degrees (2%). Over two-thirds (68%) are studying full-time and 32% are studying part-time. Last major revision: 9 February 2024; Not for publication on public websites or outside of the subject 1 Abi Brooker PhD The University of Melbourne January, 2024 Approximately 75% identify as female, 23% identify as male, and 2% identify as non-binary. These proportions are likely to slightly change by the time of students' data analysis class (Lab Class 3). Measures The data collected in the survey measure participants' demographic information, language abilities, cognitive control, and psychological wellbeing. Demographic information. The first section of the survey includes single-item questions about participants' age (an open type-in space), gender (male, female, non-binary, genderqueer, prefer not to say), enrolment status (domestic, international), enrolment type (full-time, part-time), and course name (Graduate Diploma, Bachelor Degree, or Other). A note about the "age" variable: Age is a continuous (i.e., not categorical) demographic variable. When we create your dataset, we will create a categorical "age" variable by examining the distribution of age within the sample, and then dividing the sample into meaningful and reasonably sized age categories. If you are using "age" in your analysis, make sure you use the categorical variable and not the continuous variable. Linguality. The second section of the survey comprises four questions about participants' language abilities: 1. Language use. Participants indicate how many languages they use (e.g., speak, listen, read, write) regularly (e.g., multiple times a week), with three options: one language (i.e., monolingual), two languages (i.e., bilingual), or three or more languages (i.e., multilingual). This variable is used in the first chi-square analysis. 2. 3. First language. Participants indicate whether their first language (i.e., their native language) is English, or whether it is another language. There is an optional type-in space that participants can use to write their first language. Balance. Bilingual and multilingual participants indicate whether their linguality is ‘balanced' (i.e., equally fluent in two or more languages) or 'unbalanced' (i.e., more fluent in one language than others). 4. Languages used at home. Participants indicate whether one, two, or more than two languages are spoken at home. This variable represents the family's genetic and environmental influence on participants' language abilities. 5. Languages used with friends. Participants indicate whether one, two, or more than two languages are spoken with friends. This variable represents the influence of the participants' social environment on their language abilities. How to use the demographic and linguality variables: Students can use the demographic questions and the linguality questions in three ways: • To define the characteristics of the sample in their report's Method section; • To identify a specific group within the sample for their second analysis. The first analysis focuses on participants who answered an N-back trial question correctly. In the second analysis, students might prefer to focus their second analysis on a different group, such as participants who are international students, or Graduate Diploma students, or under the age of 25, or whose primary language is English. As a variable in their second chi-square analysis. The first analysis investigates the relationship between linguality (the number of languages that participants speak) and cognitive control. Students might want to use their second analysis to investigate the relationship between one of these variables and a demographic feature, such as gender, biological age, or enrolment status; or to investigate the relationship between a variable from Hypothesis 1 and a different measure of participants' language abilities. Cognitive Control. The third section of the survey measures “cognitive control”: a person's ability to manage thoughts, process relevant and irrelevant information, and focus on goal-directed behaviour. In the survey, cognitive control is measured with an N-back task (an example of the N-back task is provided here.) The N-back task is presented as follows: 1. Instruction: Participants read a definition of the N-back test, along with an example. 2. 3. Trial: Participants demonstrate their understanding of the task by answering a question about the example. Note: Participants who answer this question incorrectly will be excluded from the first analysis because they have not demonstrated that they understand the task. Task: Participants watch a time-limited sequence of 15 items and indicate when the current item on the screen matches the item shown n-items earlier. If participants do not respond within 3 seconds, the survey automatically Not for publication outside of the subject or on public websites 2 Abi Brooker PhD The University of Melbourne moves to the next word in the sequence. January, 2024 Participants' responses are scored as the percentage of 15 items correctly identified. For example, if a participant makes three errors or three non-responses, they will receive a score of 12/15 = 80%. When we create your dataset, we will create a categorical "Cognitive Control" variable by examining the distribution of scores within the sample, and then dividing the sample into three meaningful and reasonably sized categories (higher control, medium control, lower control). This variable is used in the first chi-square analysis. Psychological wellbeing. The fourth section of the survey includes the 14 items from the Warwick-Edinburgh Mental Well- Being Scale (WEMWBS; Tennant et al., 2007). Participants rate 14 items about their psychological wellbeing, on a scale from 1 = "None of the time” to 5 = "All of the time". When we create your dataset, we will sum these 14 items together to create a single wellbeing score for each participant, ranging from 14 to 70 with a midpoint of 42. We will create a categorical "wellbeing" variable by examining the distribution of these wellbeing scores within the sample, and then dividing the sample into meaningful and reasonably sized wellbeing categories. Students are welcome to use this variable for their second chi-square analysis. Distractions. The final section of the survey includes four questions about how participants completed the survey, including the type of device used (lap top or computer, smart phone, Ipad or tablet), their environment's noise level (quiet, noisy), people around the participant (no one, a few people, many people), and participants' difficulty concentrating (very difficult, difficult, normal, easy, very easy). We include these variables so that we can monitor whether and how environmental conditions affected participants' cognitive control. How to use these variables: Similar to the demographic and linguality variables, students can use these 'distraction' variables to: (i) describe the sample characteristics, and (ii) select a specific group for their second analysis. For example, students might prefer to focus their analysis on participants who were alone, or participants who found the task relatively easy. However, we do not encourage students to use any of these 'distraction' variables as a variable in their second chi- square analysis (i.e., as a variable comprising the columns or rows of the cross-tabulation). Procedure The survey is designed to be completed in less than 15 minutes. It can be completed on any computer or device that has an internet connection. The procedure for the study is as follows: • Data collection: a five-week period spanning from two weeks before the semester to three weeks into the semester. Invitations to participate: о The subject coordinator role: invite students to complete the PSYC20008 Lab Report Survey via email announcements. о The subject tutors' role: discuss the survey PLS with students in the first lab class (Week 1). This discussion is an opportunity for students to learn more about the study aims and variables and to ask questions about the study. The students' role: complete the survey within the first three weeks of the semester. Responses completed after this time will not be included in the study dataset. Information about the study: ○ Lecture 2 (Week 1) introduces students to background information about the study, as well as a rationale for the first hypothesis and potential second hypotheses. • О The Plain Language Statement and the PSYC20008 Lab Report Guide are shared with students. Data management (Week 3 - 4): The subject coordinator role: Close the survey (Week 3). Download survey responses, process and organise the data, delete missing cases or non-genuine cases, and transform continuous variables into categorical variables. Data analysis (Weeks 5 – 7): - О The subject coordinator role: Provided the final dataset to students and tutors. The subject tutors' role: Guide the students through analysis 1. Help students troubleshoot analysis 2. ○ о The students' role: run and interpret analysis 1. Run and interpret analysis 2. Not for publication outside of the subject or on public websites 3 Abi Brooker PhD The University of Melbourne January, 2024 Data Analysis Chi-square tests of independence assess whether there is a statistically significant relationship between two (or more) categorical variables, where each variable has two (or more) levels of measurement. For each analysis, students will: (i) select a specific group within the sample; (ii) choose two variables of interest; (iii) report the distribution of those variables, for that specific group; (iv) create a contingency table with observed counts, expected counts, and standardised residuals that cross-tabulates their two variables of interest for their subset; (iv) use chi-square analysis to determine whether there is a significant relationship between the two categorical variables presented in the table, and (v) use the standardised residuals to determine whether differences between observed and expected counts are significant. More information about how to do this will be provided ahead of Lab 3. For Hypothesis 1, the variable “N-back Trial” variable will be used to select a specific group of the sample comprising only participants who answered the trial question correctly. A chi-square test of independence will be used to test the relationship between linguality (monolingual, bilingual, multilingual) and cognitive control (higher, medium, lower). Standardised residuals will be used to reveal any significant differences between observed and expected counts within the contingency table. Students will work together in Lab 3 to run and interpret their first analysis. For Hypothesis 2, students can use any variable to select a specific group within the sample. A chi-square test of independence will be used to test the relationship between two categorical variables. Standardised residuals will be used to reveal any significant differences between observed and expected counts within the contingency table. References and sources Students are expected to use between 6 and 12 refereed journal articles to support the rationale of their lab report. We advise that students use a combination of the following papers as a basis for their literature research. These readings are available in Readings Online. Antón, E., Carreiras, M., & Duñabeitia, J. A. (2019). The impact of bilingualism on executive functions and working memory in young adults. PloS one, 14(2), e0206770. https://doi.org/10.1371/journal.pone.0206770 Bialystok, E. (2017). The bilingual adaptation: How minds accommodate experience. Psychological Bulletin, 143(3), 233–262. https://doi.org/10.1037/bul0000099 Filippi, R., & Bright, P. (2023). A cross-sectional developmental approach to bilingualism: Exploring neurocognitive effects across the lifespan. Ampersand, 10, 100097. https://doi.org/10.1016/j.amper.2022.100097 Teubner-Rhodes, S. E., Mishler, A., Corbett, R., Andreu, L., Sanz-Torrent, M., Trueswell, J. C., & Novick, J. M. (2016). The effects of bilingualism on conflict monitoring, cognitive control, and garden-path recovery. Cognition, 150, 213-231. http://dx.doi.org/10.1016/j.cognition.2016.02.011 Van den Noort, M., Struys, E., Bosch, P., Jaswetz, L., Perriard, B., Yeo, S., ... & Lim, S. (2019). Does the bilingual advantage in cognitive control exist and if so, what are its modulating factors? A systematic review. Behavioral Sciences, 9(3), 27. 10.3390/bs9030027 Wang, J., & Wei, R. (2023). Is bilingualism linked to well-being? Evidence from a big-data survey. Bilingualism: Language and Cognition, 1-11. https://doi.org/10.1017/S1366728923000603 Not for publication outside of the subject or on public websites Abi Brooker PhD The University of Melbourne Assessment criteria A. Title and Abstract Note: Abstract should be no longer than 10% of your overall word limit (i.e., 150 words). A1. Title Content A2. Abstract January, 2024 (10%) • Clearly and concisely outlines the main topic of the research, including the relationship between key variables. 2% Provide a brief, comprehensive summary of the paper in a paragraph. The summary includes a concise description of: 8% - the problem under investigation (i.e., the research topic). relevant sample characteristics (e.g., number of participants, age, gender composition) and essential features of the study method (e.g., study design, outcome measures, data-gathering and analysis procedures). the main findings, including effect sizes and statistical significance levels (i.e., p values), where appropriate. the implications of the study's findings with regard to the problem under investigation. B. Introduction B1. Opening (25%) Opens by introducing the problem under investigation and outlining its importance. 5% B2. Literature Review (Relevance and • Provides a succinct and focused review of literature relevant to the problem. 8% Understanding) • Summarises key background information accurately and in appropriate detail. B3. Literature Review (Rationale) B4. Aims and Hypotheses • Develops a cogent rationale by critically evaluating the literature and explaining how the current study builds on prior research. Outlines the purpose and scope of the study and generates specific hypotheses for testing. 7% 5% C. Method (3%) Note: Method is expected but is not included in the 1500-word limit. C1. Participants Describes the participants involved in the research. In most cases, this includes: 1% number of participants in total and in relevant subgroups for analyses descriptive statistics for years of age gender composition of the sample other major demographic characteristics as warranted by the study eligibility and exclusion criteria C2. Materials and Measures Describes all outcome measures, and the materials used to derive them, with sufficient detail to facilitate reproducibility. 1% C3. Procedure and Design Describes the procedures that were carried out in the study, including the specific steps involved in collecting and analysing data and a detailed outline of how participants were allocated to groups or categories. 1% Not for publication outside of the subject or on public websites 5/n Association Between Age and Number of Older Siblings on False Belief Understanding [Author name removed] Melbourne School of Psychological Sciences, University of Melbourne PSYC20008: Developmental Psychology [Tutor name removed] [Due date removed] Word count: 1522 1 2 Abstract Age and number of older siblings are variables suggested to influence theory of mind (ToM) development. To test the relationship between these variables on false-belief understanding (FBU), PSYC20008 students interviewed 320 children (aged 3 to 5), using a modified version of the Sally Anne task. Chi-squared testing indicated that there was a significant association between FBU and age. However, a significant association did not exist between FBU and number of older siblings. These results support the theory that children develop false-belief understanding at approximately four years of age, but do not support the theory that sibling presence can enhance this development. Future research could consider older sibling cognitive sensitivity as a factor influencing the development of false belief understanding, rather than just the number of siblings. Keywords: Theory of Mind; False Belief; Age; Sibship; Developmental Psychology. 3 Theory of mind (TOM) is the ability to represent one's own mental state and the mental states of other people. It involves understanding the relationship between a person's behaviour and their thoughts, beliefs, and emotions (Devine & Hughes, 2016). ToM informs how well people understand each other, and how people form positive social relationships (Prime et al., 2016). An important early part of ToM is false-belief understanding (FBU). A child has FBU when they recognise that people's beliefs about events around them can be incorrect. Understanding the experiences that are related to ToM and FBU can help reveal the extent to which biological, and environmental, experiences contribute to ToM development. Early research indicated that ToM develops with biological developments. Wimmer and Perner (1983) investigated the relationship between age and FBU with children aged between 3 and 9. Children aged three and four were unable to demonstrate FBU, however, children aged 5 demonstrated FBU. Wellman et al. (2001) replicated Wimmer and Perner's study and found similar results, reporting that FBU improved with age. Both of these studies support the theory that ToM develops alongside other biological developments, and that older children are more likely to demonstrate FBU than younger children. Despite their clear support for a biological model of ToM development, neither Wimmer and Perner (1983) nor Wellman et al. (2001) considered the relationship between environmental factors and ToM development. There is increasing research evidence to suggest that, alongside biology, nurture plays an important role in ToM development (Prime et al., 2016; Slaughter, 2015). Some environmental experiences that are likely to contribute to ToM include language, sibling environment, and parenting behaviour. A longitudinal study by McAlister and Peterson (2012) found a positive relationship between a child's FBU and the number of siblings living with the child (i.e., the child's ‘sibship'). The results indicated that children with more older siblings had advanced FBU. This suggests that siblings can 4 contribute to ToM development, perhaps through interacting with the child and modeling different mental states. A potential limitation of McAlister and Peterson's (2012) experiment was that the age of their participants was limited, which meant that they could not infer about advanced levels of ToM. Kennedy et al. (2015) addressed this limitation by including children between the ages of 4 and 11. They found that children with more older siblings could more accurately explain how past experiences influence current beliefs. These studies suggested that throughout childhood, having more older siblings improved the development of ToM. Sibship size might not be the only family experience that relates to ToM. Devine and Hughes (2016) argued that the age of the siblings mattered as well. In their meta-analysis of 93 studies of children aged three to seven, they found only a moderate association between sibship size and FBU. The relationship was stronger when children had more ‘child aged' siblings. Studies investigating ToM indicate that there might be associations between FBU and age, and FBU and number of siblings, however few studies have investigated both of these relationships with the same sample. A study addressing whether siblings matter for children at the time that they are developing ToM (aged 4) would be useful for addressing both of these relationships together. The aim of the current study was to examine the relationship between age and FBU, as well as the relationship between sibship and FBU. There were two hypotheses: 1. Among children who understand the false-belief task, there will be a statistically significant relationship between age and FBU. More five-year-olds will demonstrate FBU than expected by chance. Fewer three-year-olds will demonstrate FBU than expected by chance. 2. Among four-year-olds who understand the false-belief task, there will be a statistically significant relationship between sibship and FBU. More children with >2 siblings will demonstrate FBU than expected by chance. Fewer children with 0 siblings will demonstrate FBU than expected by chance. Method 5 Participants Participants were children who were known by at least one PSYC20008 student. PSYC20008 students interviewed 615 children (301 girls, 314 boys). There were 174 three- year-olds, 240 four-year-olds, and 201 five-year-olds. Of the 615 children, 193 had no siblings, 239 had one sibling, and 183 had two or more siblings. Materials The materials used in this study were: a cardboard M&Ms container, small pencils, and an Interview Schedule (as shown in Appendix 1). Before the interview, the M&M container is emptied and the pencils are placed inside the container. A plain language statement and consent form were also used to discuss the study with the child and the child's caregiver. After discussing the study and its aims, the caregiver signed the consent form and returned it to the student interviewers. Procedure A pair of PSYC20008 student interviewers conducted the interview with the child. One student took the role of interviewer and the other student took the role of scribe. Before the interview began, and in consultation with the caregiver, the scribe took notes about: the child's age (in years and months), gender, hours spent away from home, number of siblings, and age of siblings. The interview was conducted in a quiet place. The child's caregiver was also in the room but was asked not to participate in the interview. The interviewer chatted with the child

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Instructions Need this work in 1500 words | single spaced Level of writing - Sophomore Refer to attached guide and sample for detail. data is attached. Referencing style is APA, make sure you meet all the requirements of apa. use the template to write the hypothesis and the report. example is attached. use the required