Galotti interviewed students of different ages about two types of goals. The first type focused on timing, such as what they wanted to accomplish in the next day, week, or month. The second type focused on category, like whether they had goals related to school, family, or other areas of life. The results showed that older students were more likely to set goals related to specific timeframes and responsibilities, such as schoolwork and chores. Younger students, on the other hand, tended to focus more on goals related to personal interests and hobbies.

One thing the authors could have looked into more is how a person’s culture, family income, and family dynamic affects how they set goals and make plans. Students who come from families or cultures with a stronger emphasis on schoolwork may have more homework/grades related goals than those who don't. They also could have studied how emotions or motivation, like confidence or support from family, play a role. Watching the same people over time could have shown how decision-making skills grow. It might also help to include older people, like young adults, to see a fuller picture of how these skills develop.

I would create a long-term study that follows people from age 8 to 25. It would include people from different cultures and backgrounds. Every two years, they would do interviews and activities to see how they make decisions and set goals. The goal is to learn how things like family support, confidence, and cognitive development/age affect how these skills grow over time.

In the study by Deanna Kuhn (1977), children aged 6 to 14 were asked to evaluate conditional reasoning problems. These included logic-based questions like, “All who live in Tundor are happy. Jean lives in Tundor. Is Jean happy?” Children were tested on their ability to understand logical structures like modus ponens and modus tollens, as well as common errors like affirming the consequent. The results showed that reasoning ability improved with age, but performance also varied depending on the format of the logical problem; some types were more difficult than others.

This study focused on age-related differences, but it didn’t account for educational background, cultural context, or working memory capacity, all of which could impact how children reason. It also didn’t test how children’s reasoning may differ when they collaborate with peers or adults. Including those factors might have revealed more about the role of environment and interaction in developing logical thinking.

I would say a cross-cultural, mixed-methods study that tracks children aged 6–14 over several years. It would include both individual and group reasoning tasks, using logic puzzles in multiple formats and contexts, like social vs. academic. The study would measure not only correct responses but also children’s verbal explanations, offering insight into how they reason through logic problems. It would also include variables like parent education level, school curriculum, and working memory.

Gauvain and Rogoff evaluated children's decision-making abilities at different ages by having 9-year-olds and 5-year-olds examine a model of supermarket in order to determine the most optimal route for collecting specific items and comparing how much longer each age group's route was than the actual optimal route. The results were that 5-year-olds chose routes that were 2.6 times longer than the optimal route and 9-year-olds chose routes that were 1.5 times longer than the optimal route, and the 9-year-olds spent more time scanning the map/model. This shows some possible correlation between age and better decision-making (planning) skills.

The authors of the study could have explored older age groups than 9-year-olds to see if the correlation is really between age and planning abilities.

For my study I would study children who were 5, 9, 13, and 17 years old and ask them to plan (using a paper map with a scale on it and not an app or GPS device) to plan the optimal route for delivering various packages to people if they were a delivery driver for FedEx within a 5 mile radius (with the houses they need to deliver to marked and scattered throughout the map randomly). I would see how much longer or potentially shorter their route was compared the actual optimal route. Then I would repeat this test with different neighborhoods/areas to see if this trend continued regardless of location.

In this study Carey is discussing a 'naïve theory approach' which is that children construct commonsense understanding or theories that have individual concepts embedded in them and it is developed by the existing knowledge that they already have.

• She is discussing an approach in talking about children's developing knowledge of biological concepts. Carey is arguing that children's understanding of what living thing undergoes tremendous change between 4-10 years. E.g., preschoolers have concepts of animals and people that are organized very differently from the way adolescents and adults organize these concepts.

• Preschoolers know what an animal is by making analogies to humans

• E.g., human mothers take care of their human babies so mama cub takes care of baby cub.

What else could they have done in this study?

• Carey could have done different age groups maybe adolescents to adults and seeing adolescent analogies to adult analogies.

• Maybe seeing the change in a child when they go from elementary to middle school or middle school to high school and seeing how their brain develops.

Design a study

• In my study I would want to evaluate elementary age children specifically 10-12 years of age going into middle school 12-14 years of age. I would like to do boys and girls separate then together. Seeing if their 'naïve theory approach' would differ and if their analogies would differ depending on who their friends are and who they hangout with and if they have good grades.

In Deanna Kuhn's 1977 study, she explored how children of different ages respond to classical reasoning questions. She worked with children aged 6-14, and her findings were that performance on types of reasoning varied depending on age and the kind of question. For example, 1st graders performed the best in Modus Ponens and Modus Tollens, but the worst when looking at all classical reasoning problems. Overall, it was found that age did not serve as an accurate predictor of performance.

I would have liked to see all of the results in this study. The first is that the results given to us in the lecture only go to 4th grade, which is not up to age 14. Another thing that the authors could have explored is controlling for developmental pace. Not all children develop equally, and some of the variations in results among the different grades could be due to certain developmental delays or acceleration.

For a follow-up experiment, I recommend that there be 3 groups of children within the age ranges.

~Group A would be "on-time developers" (e.g., 1st graders who show cognitive patterns consistent with expected norms for their age)(e.g., 1st graders who show cognitive patterns consistent with expected norms for their age)

~Group B would be "early developers",. (showing reasoning abilities or cognitive skills ahead of their grade level)

~Group C would be "late developers". (showing delayed reasoning or cognitive patterns for their age group).

We would separate the children based off of developmental milestones that have been reached either early, on time, or late.

The study by Gauvain and Rogoff (1989) evaluated children's planning abilities by having them navigate a model supermarket to collect items using the most optimal route. The results showed that older children (9-year-olds) used the map more effectively and chose more efficient routes only being 1.5 times longer compared to younger children (5-year-olds), who took paths that were 2.6 times longer. This suggests that planning skills improve with age, as older children exhibit better spatial awareness and strategic problem-solving.

Pairing children up could show whether teamwork leads to better planning and shorter routes. Adding a prize might reveal if motivation helps them strategize more effectively. Using a touchscreen instead of a model supermarket could test whether digital navigation improves spatial awareness. Each change offers deeper insight into how children develop planning skills.

Pairs of children, either two 5-year-olds or two 9-year-olds, navigate a touchscreen simulation of a supermarket to examine how digital navigation influences planning efficiency. Researchers have a reward system, where children receive a prize for the shortest route, encouraging strategic decision-making. Route length, time taken, hesitation points, and eye movements are tracked to assess how collaboration, motivation, and digital interaction impact planning skills. This setup evaluates whether two children together plan more efficiently than an individual in a digital environment.

The study I chose was Zelazo and Carlsons Hot and Cool Executive Function in Childhood and Adolescence: Development and Plasticity (2012). They evaluated the development of executive function in children by reviewing research on how cool (emotionally neutral) and hot (emotionally charged) executive processes emerge. They synthesized findings from multiple studies, highlighting that cool executive functions like working memory, inhibitory control, and cognitive flexibility show major improvements during middle childhood (ages 6-12), allowing children to reason more logically and make more deliberate decisions. In contrast, hot executive functions related to emotionally driven decision-making, such as resisting immediate rewards or making decisions under emotional pressure, continue to develop more slowly and mature into adolescence (around ages 13-18). Their results suggest that reasoning abilities tied to logical thinking strengthen earlier, while emotional decision-making becomes more refined later. They supported these conclusions by discussing experiments such as delay of gratification tasks and cognitive flexibility games that measure how children's self-control and decision-making abilities change with age.

The authors mainly focused on middle childhood and adolescence, but they could have compared younger age groups, especially early childhood (ages 3-5), to better understand when hot versus cool executive functions first begin to diverge. They also could have explored how cultural factors influence hot EF development, since emotional regulation and decision-making styles can vary across cultures.

New Study Proposal: I would design a longitudinal study that tracks children starting at age 3 through age 15, measuring both hot and cool executive function every two years. I would include children from diverse cultural backgrounds to examine whether the development of emotional decision-making differs depending on cultural norms around emotion expression. Tasks like delay of gratification and risky decision-making games could be used across ages.

Inhelder & Piaget conducted a study on children under the age of 8. The study included a comprehensive introduction allowing the children to identify between daisies, roses, and flowers. Within a chart they added four roses and two daises. Then asked the children if there were more flowers than roses. The results concluded the difficulty children have in differentiating between parts and wholes, as they answer there is more roses than flowers. In addition, Piaget adds that a child up until the age of 8 can compare only within two entities.

Within the study, I believe the authors could have explored with different variables. Variables more familiar to the children would have made it more evident that the children could not differentiate between parts and a whole or between more than two variables.

To revaluate this study, I would choose children within the age group of 6 to 8. Then, I would have children choose within their favorite foods. Considering their current diets are highly limited to fries and chicken nuggets for the sake of this explanation I will be considering it their favorite food. I would again include a comprehensive introduction to the experiment, having children identify between fries, chicken nuggets, and food. Then I would set out 3 pieces of chicken nuggets and 2 of fries. Then ask if there are more chicken nuggets than food. Children begin eating ever since birth, food is something they are completely familiar with, this would actually make it evident if children were not capable of identifying between parts and a whole, in addition to comparing only within those two entities.

The 1977 research by Deanna Kuhn examined conditional reasoning problem evaluations from children between ages 6 to 14 to determine their mastery of modus ponens and modus tollens logical structures. The participants read statements that read “All who live in Tundor are happy” followed by the comment on Jean's residence in Tundor. Jean lives in Tundor. Is Jean happy?” Logical reasoning abilities reveal that older children make correct deductions while younger children frequently affirm the consequent according to research findings.

The research made strong progress showing how logical reasoning ability changes with age but its findings could have expanded if the study included younger test subjects to determine emergence stages or added realistic mental mindsets to observe contextual logical processing. The study's results would possibly have been strengthened through analysis of cognitive ability performance differences between children from different educational backgrounds.

I would create a longitudinal project using children between ages 4 and 18 who come from different educational institutions. The subjects would complete conditional reasoning tasks through abstract logical tests along with examples based in real-life circumstances containing emotional elements. The evaluation of cognitive processes during reasoning tasks can be achieved through eye-tracking along with neuroimaging techniques which helps researchers identify how participants reason as well as their decision-making mistakes.

In her 1977 study, Deanna Kuhn evaluated how children develop the ability to reason logically about hypothetical situations and problem-solving. She found that older children, particularly those in middle childhood, were more capable of using logical reasoning when solving problems involving multiple variables, compared to younger children. The study showed a clear developmental progression in cognitive abilities related to reasoning.

The study could have explored different age groups, including adolescents and adults, to see if and how reasoning abilities continue to develop. Additionally, it could have tested the impact of different variables like the role of social influence on problem-solving or how cognitive load affects reasoning abilities. Another approach could involve comparing different experimental designs, such as tracking reasoning development over time, rather than just a cross-sectional approach

To design an experiment, I would do a longitudinal study comparing reasoning abilities across a bigger range of age groups, from early childhood to adulthood. I would introduce variables like group versus individual problem-solving and measure how social interactions influence the logical reasoning someone has. This study could provide a deeper understanding of cognitive development and how external factors contribute to problem-solving skills across a person’s life.

The study that I chose was the Inhelder and Piaget study from 1996 that looked at class-inclusion class. The study took students and showed them 6 flowers, 4 roses, and 2 daisies. They first asked the children how many roses there were, how many daisies, and how many flowers. They found that up until the age of 8, children will state that there are more roses than flowers. Piaget states that “children will have difficulties distinguishing the difference between parts and a whole. During this time, “[children] can only compare two entities.” In conclusion, Piaget says that “children [at this age] cannot distinguish between parts and wholes.” 

Something they could have done to change the study is to use a different variable, like colored marbles. I wonder if children would have the same difficulties in distinguishing the difference between parts and a whole. Would they come to the same conclusion if just the type of object changes?   

First, conduct the same study that Inhelder and Piaget conducted with the flowers. Next, you show children ages 2 to 8 some marbles. There are 6 total marbles, 4 white marbles, and 2 blue marbles. You ask the children how many colored marbles they see. Next, you ask the child if they see more colored marbles or more marbles in general. This way, you can test to see if the children are still having difficulties with parts from the whole, but also to answer the question of does the same thing happens when the variable changes the change from flowers to marbles. Something that may also be interesting is do children consider the color white a color.

I chose to focus on the study conducted by Chavajay, P., & Rogoff, B. (2002). This study seeks to explore how Mayan mothers of various educational backgrounds interact with their children and how those interactions differ. The study’s findings suggest that mothers with minimal schooling engage in a more passive parenting style, with no clear authority figures, instead favoring a collaborative approach. On the other hand, mothers with greater schooling tend to engage in a more hierarchical-based parental relationship. This is also reflected in the division of labor: those with minimal schooling participate in a multiparty approach, while those with more schooling engage in role assignment. The study aims to establish whether formal Western schooling shifts traditional indigenous ways of collaboration, specifically in regard to hierarchical problem solving.

When seeking to evaluate this study and potential changes it would be interesting to see how the findings vary amongst a diverse age group of children. It also would be interesting to see if father's presence and education level influences hierarchical dynamics.

If given the opportunity to conduct this study on my own, I would conduct a longitudinal study tracking how this dynamic changes throughout childhood and would include both mothers and fathers. I would seek to explore if parent interaction style shifts during childhood milestones and wether they maintain collaborative approaches.

This study was a supermarket study done with 5-year olds and 9-year olds. In this study, the children all had to study the same map. The main goal of this study was to see which age could have the fastest route with the grocery list that was given. The results showed that the 9-year olds had a faster route which meant they could plan more accordingly than a 5-year old. The 5- year olds had a 2.6 times longer route. The 9-year olds studied the map longer.

There are a couple things that I thought about that could be different or other things that could be tested and compared.

• Comparing a map of the grocery store that, that child attends to the map they originally studied. Would the child have a faster route since they would already be familiar with that store?

• Using these age groups but studying the time difference between boys and girls as well as comparing the 5 and 9- year olds.

I would design a study where they study the map that was originally given with the list included. Once that study was concluded, I would then give them the same list, but let them go their store and test it out in person. Would there route be the same? Would it be faster considering they are familiar with their surroundings? I would then compare the times of studying a map vs physically getting through the store with the list.

In module 6 topic 1 we are learning about higher order cognitive skills such as reasoning. In a 1977 study by Deanna Kuhn worked with children ages 6-14 to evaluate their reasoning. She asked these children classical reasoning questions such as, "All who live in Tundor are happy. Jean lives in Tundor. Is Jean happy?" Results from grades 1-4 showed that performances varied according to the format of the problem.

I would have liked to see the results of everyone in this study. Why would you study up until 14 and not use the data from the age range? I would also like to see a wider age range in early childhood. Such as starting the study at 3 instead of 6.

I would perform a longitudinal study examining children's reasoning between the ages 3-10. I would be examining the same group of children for a long period of time. I believe between these ages substantial growth happens and we could easily measure that growth this way. This would provide a great example of how reasoning changes through early childhood into late childhood.

Deanna Kuhn studied and evaluated kids that were ages 6 to 14. These kids were evaluated based off some questions, some being, "All who live in Tundor are happy. Jean lives in Tundor. Is Jean happy?" The results would then how that the children's reasoning improved as they were older but depending on the format of the question, the performance could vary. This would help show children's logical understanding of structures like the modus tollens or modus ponens.

This study focused on the age of children and how each age/stage of life affected the children's logical understanding of structures. But I feel as though the study could have benefited following the children throughout their middle childhood. If they followed the same children as they developed, asking the same/similar questions. I feel the study could've really shown how children mature and begin to think logically.

If I were to do this study I would take a group of kids all aged 6. My study would include kids of all different backgrounds, from those who are privileged to less privileged. As well as different races and ethnicities. These kids would be questioned either semi-annually or annually. The question would be relatively the same or close to Deanna Kuhns question.

I chose to evaluate Deanna Kuhn's (1997) study on conditional reasoning. This study involved children from ages 6 to 14, and were asked logical questions such as " if all who live in Tundor are happy, and Jean lives in Tundor, is Jean happy?" Through this study Kuhn concluded that the formatting of the questions asked was the main cause of performance variation, not just the child's age. This means that the older children didn't always perform better, it all lied within the questions formatting and structure.

I wonder if children would reason differently to emotion based questions instead of pure logic. In my opinion, Kuhn's study could have gathered more information if she looked at emotional reasoning and not only logical reasoning. Asking questions that involve feelings with real life choices and not only abstract 'if/then' situations. I believe answers would change if feelings and emotions were involved. It would be interesting to see how younger kids(4-5 year olds) perform compared to older teens (16-17), a greater age group compared to Kuhn's original study (6-14 year olds) could show different reasoning patterns. Another interesting idea/approach could be adding a time limit or pressure to see if rushing changes how kids reason.

In my study I would ask two types of reasoning questions: one pure logical and one emotional, real life scenario. My participants would be children of the ages 4-17 to widen the age gap between participants to see the stark differences or similarities. In order to add the pressure of a time constraint, I would have one set of participants with no time limit, while the other would have to answer within a time-constraint. In this study I would be comparing how emotion and the pressure of time affect the performance and reasoning patterns within the widened age groups. I hope to find how logical and emotional reasoning develop or change within stress/pressure and based on age as well.

Gauvin & Rogoff (1989) gave children the task to find the most optimal route to collect items in a map model of a supermarket with the only rule being you cannot ‘fly’ across the map. Results showed that older children (9 years old) tended to scan the map more while younger children (5 years old) used routes that were 2.6 times longer than the optimal route. In conclusion, they found older children were more likely to scan and utilize more optimal routes suggesting better skills at planning and optimal decision making. 

It might show helpful results to experiment on different age group variables with older children being up to 11 or 12 years old and the youngest being 4 or 5. Showing the map and allowing the child to find the optimal route is helpful in understanding decision making in middle childhood however, it may be helpful to solidify results and further understand decision making processes by putting the children in a real ‘store’ situation that they must navigate. 

In my version of this experiment, I would keep the map task as it gives great insight into how a child scans and thinks about the most optimal plan to get around the supermarket. I however, would take it a step further and place the child in real life store conditions with the same map and perhaps a time limit condition to see if they continue to follow their plan to be able to get the items in the task in the amount of time given. I would test a variety of children from 4-12 years old and with an even amount of children of different genders as this may take the study another step further in the understanding of children's decision making and planning. 

They wanted to understand if and how a child's cultural background affects attention and learning and if the mother's amount of formal education would or would not affect the child's learning. They observed how Mayan mothers helped their children solve puzzles. They found that mothers with less formal education were more likely teach the children in a collaborative way and noticed the children being more observant. The mothers with more formal education were directive in their teaching, giving tasks to children and categorizing in a hierarchical way.

A way in which I think they could have done something differently is by asking someone other than their mother to teach them. Observing any differences if a father or a different caretaker helped with the puzzle would be interesting.

I would change this study by instead of using Mayan mothers to teach the children, I would have the fathers teach a basic skill. I would ask for a task such as fishing, building, or any other culturally appropriate task. I would then observe how the child watches and participates using the same measures of attention and learning. I would be interested in observing different patterns based on gender roles and how that might affect learning.

I chose The Inhelder and Piaget 1964 study on class inclusion where they looked at children up to the age of 8. They asked the kids to decipher between the flowers, rose, and daisies. The results showed that children up to 8 claim that there are more roses than flowers so it is determined that they have a hard time distinguishing parts from wholes and can only compare 2 entities at a time in this case either roses or daisies. 

 Inhelder and Piaget could have expanded their study by including different age groups, such as younger children under 4 and older children over 10, to better track how the understanding of parts and wholes develops over time. They also could have introduced different variables, like using familiar objects (e.g., toys, animals, foods) instead of just flowers, to see if familiarity impacts children's ability to correctly answer class inclusion questions. Another idea would have been to test different experimental designs, such as giving children more time to think or using visual aids to see if that changed their responses.

I would design a larger study that includes children ages 3 to 12. I would test them using a variety of familiar and unfamiliar objects, asking class inclusion questions similar to those used by Inhelder and Piaget. I would also add a visual aid condition for some participants to see if it improves their ability to recognize parts and wholes. This would help show how age, familiarity, and extra support affect class inclusion understanding.

Kuhn evaluated conditional reasoning. She did this by seeing how children aged 6-14 responded to classical reasoning questions. She found that the results from the reasoning experiment varied depending on the format of the problem. For example, first graders performed exceptionally well on the Modus Ponens (basic valid reasoning) but underperformed on the Denying the Antecedent category, which involves invalid reasoning. Overall, there was no relationship between overall reasoning and age group, as the second graders performed the best overall, which is counterintuitive.

The authors could have explored the relationship between age and invalid reasoning more. Why did even fourth graders struggle with affirming the consequent? It would be interesting if the authors explored why this logical error persists.

To determine whether the Affirming the Consequent logical error is developmental or not, we can conduct a study on this topic. I would run the same experiment, focusing solely on this logical error, and create an instructed group and a control group. The instructed group would receive one week of brief lessons on logical reasoning, specifically on affirming the consequent. The control group would receive their basic lessons without a focus on logic. I would then administer another test to both groups and compare the results. I would also do a follow-up test after one month to see if the instructed group sustained this knowledge. This would demonstrate whether explicit teaching can correct this common logical problem.

In 1977, Deanna Kuhn wanted to study conditional reasoning in children ages 6 to 14. To do this, she asked these children a series of questions, one of which was, "All who lives in Tundor are happy. Jean lives in Tundor. Is Jean happy?" All of the questions asked in the study reflected the ideas of different logical fallicies used in philosophy. The study revealed that there was a linear relationship between the ages of the children and the correct answers to the questions that were being asked. Typically, older students actually performed lower in the study compared to the younger students, and second graders performed the best out of all the ages. The findings in the study concluded that the format of the problem being proposed to the children was what determined their performance, it was not necessarily their age.

I think the study could have done a few things differently in order to ensure the validity and reliability of this experiment. First, I think the education and socioeconomic status of the children could have been taken into account. Some children may have received less education, or not as great of an education, as some of the others in the study which might have been indicative of their wrong answers. I also think Kuhn could have expanded the age range even further, possibly starting at 4 or 5 years old, to further emphasize the fact that younger children performed better than the older children.

If I were to recreate this study, I would start by gathering a wider age range of children starting at 4 years old and going to 17 or 18 years old. I would also administer surveys to the children before the study begins to gather information on their educational and socioeconomic background. I would then create about three groups using this information, ensuring I have equal representation of different ages and backgrounds in each group. Finally, I would ask similar questions to the one's Deanna Kuhn proposed in her study.

I chose the study by Deanna Kuhn (1977), which evaluated conditional reasoning in children ages six to fourteen. In this study, children answered classic logical reasoning questions, such as, “All who live in Tundor are happy. Jean lives in Tundor. Is Jean happy?”; this is an example of modus ponens. Another question asked, “All people in Tundor own cats. Mike does not live in Tundor. Does Mike own a cat?”; this is an example of denying the antecedent. The researchers found that performance on modus ponens tasks decreased with age. They also found that second graders performed the best overall. However, overall performance varied more by the format of the problem than by the child’s age.

The study could have further explored differences in reasoning based on type of schooling, such as homeschooling, public, private, charter or alternative schools, or differences in cultural background. It also could have examined how emotional content influences children’s reasoning skills, especially since emotion regulation is still developing in children at this age.  Including emotional reasoning problems could reveal whether heightened emotions disrupt logical reasoning or influence them in any way.   

I would design a study that examines how emotional content in conditional reasoning problems affects children’s logical reasoning at different ages. I would create two sets of reasoning tasks: one neutral, as in the original study, and one with emotional content. For example, in the neutral set, “All people in the store are wearing red shirts. Gina is wearing a red shirt. Is Gina at the store?” For the emotional set, “All children who have a sick pet feel sad. Tim’s pet is sick. Is Tim sad?” I would test children from multiple school settings, ages six to fourteen, with diverse cultural backgrounds. I would then compare performance across age, schooling type and emotional vs. neutral task sets to determine whether emotional content improves, impairs or has no effect on accuracy, and whether these effects vary based on age, schooling background or type of emotional content.  

The Study:

The Galotti (2005) study looked at how decisions are made. It asked various aged students about two categories of goals: Time-Based and Category based. The conclusion of this study was that older children tend to have more goals related to school and chores than hobbies. This result shows that decision-making for children starts off simple and is often based on simple choices and immediate rewards but with age they start to be more careful in their decision making and start considering future results (consequences).

In this study Inhelder and Piaget presented children with four daises and two roses. They asked children if there were more flowers or roses? This was meant to test whether children understood that both roses and daisies are a type of flower. They found that most children under the age of 8 would answer that there are more roses. Demonstrating that they didn't yet understand that "flowers" included both types. Older kids were more likely to answer correctly showing they had reached that stage of thinking where they understood parts and wholes. A stage Piaget referred to as Concrete Operational.

I think something different they could have done would be to change the categories to something other than flowers. Food or toys would expand the range and show us if it was specific to flowers or just the general cognitive development stage they're at.

If I were to conduct my own study I would have students bring in their favorite toy. I myself would bring in a box filled with legos (as my favorite toy). After each child presents their toy to their peers I will pass around a survey that students will pick their favorite toy of the day. at the end of the survey I would have a bonus question that reads, "Are there more legos or more toys?" This way the children will be engaged and excited to bring their favorite toy and we can see if they understand parts and wholes.

I chose the study that begins at 2:31 in the second video of topic two. They looked at reading and writing comprehension and how those two things are correlated. They found that the third and the fourth grade are pivotal times for reading and writing comprehension.

They could have continued the study through graduation to see how the children continued to learn and grow. We have talked about how children grow and develop through middle school, so to see how reading and writing changes would be interesting to see. We could evaluate the attachment theory and how the children's relationship with their parents affects their performance in school.

I would start a longitudinal study comparing reading and writing comprehension. I would have about 50 boys and 50 girls. I would talk to them about their attachment to their parents and figure out what attachment style they are. I would see how reading and writing comprehension differ by attachment style and by age.

In Deanna Kuhn's study, she worked with children aged 6 to 14 and evaluated them on conditional reasoning. Given classical reasoning questions such as "All who live in Tundor are happy. Is Jean happy?". Surprisingly, the results show that the second graders (who were the second youngest group in the study) performed the highest overall in answering correctly. However, the study mainly concludes that there is no definitive prediction of performance based on age group.

I feel like the researchers could have used a larger range of age groups, like seeing the differences between children in kindergarten and children say approaching middle school.

For my study, I would gather a group of 5 year olds, possibly differing in background characteristics, and ask them a few similar questions to the ones in Kuhn's study, maybe using a few more than she did. Then, I would revisit the same group of children when they have reached the age of 11, asking the same questions and comparing their previous answers to see possible changes in conditional reasoning.

Inhelder and Piaget (1964) conducted a study where children are shown six flowers, four of them being roses and two of them being daisies. They were then asked "Are there more roses or are the more flowers?" Children younger than seven years old will typically say there are more roses than flowers. The results of this experiment showed that children in the preoperational stage aren't able to differentiate categories, at least not until middle childhood.

I believe this study could be performed with different variables; instead of flowers, use toys. Toys provide sentimental value to most children, and I believe it could have provided different results compares to flowers.

I would create an experiment presenting toys - three toy cars and five teddy bears. This allows for a better correlation between kids and things they are familiar with. Following the structure of the original experiment, I would ask "Are there more toys or are there more teddy bears?" My study would consist of children between four to ten years old who would randomly be assigned to groups and given no explanation of what the items are. Also, I'd want to see if any factors may affect these skills and change their understanding such as pictures, tangible object, or even some sort of display.

In this study children are asked to define between two different types of flowers. The reason why they are asked questions to define the flowers is to check their comprehension. What they found was that ages 8 and below the child when asked would usually be able to tell the type of flowers apart, but not the difference in amount of types. This shows that the child has issues distinguishing differences when coming to parts and whole. The child can only compare two items. 

Something else the researchers could have added to the experiment to add on to the study is an older age group as well. This would allow for the study to show when the child can tell the difference between part and whole and at what age. This could also show why that growth happens. What causes the child to learn this ability and what is holding the younger child back. Is it a natural growth of understanding or is it taught to them over time.

For the study with older ages I would ask the same questions that priorly asked to children under the age of 8 to children between the ages 9-12. I would try to find some further questions along the way as well to see if there is a connection to another subject that allows the child to learn part from whole. Maybe add more items for the older children to tell apart. 

Children were shown in the study conducted by Inhelder and Piaget, done in 1964, six flours, four of which were roses and two were daises. These children were then asked a set of questions that wanted to categorize the flowers. The questions were how many roses there were, how many daisies, and how many flowers there were. Inhelder and Piaget found that young children answer that there are more roses than flowers, meaning their class inclusion is lacking. As children were unable to keep track that flowers were the categorization of rose and daisy, and flowers were the whole while roses were the parts. They focus on only the bigger number or group.

Things they could have changed is the amount of children they tested alongside what they used to test the children, such as fruit. They maybe could have explored if children know the whole more (meaning, instead of flowers that children do not constantly interact with, they use toys or something), then maybe they would get the part compared to the whole correct. I also wonder if size would change their perception of if there is more.

I would show children 11 fruits, 7 are bananas and 4 are apples. I would as the children how many fruits there are, how many bananas there are, and how many apples there are. Then, I would ask if they see more bananas or more fruits. This would ensure that the children are being asked the same criteria as Inhelder and Piaget but with a different, more familiar set of objects.

The Gauvian and Rogoff Supermarket Study looked at how cultural context influences children's decision-making. The study compared how children from two different cultures, American and Guatemalan Mayan, made choices while shopping in a supermarket. The results showed that American children were more likely to make decisions independently and focus on their own choices, while Guatemalan children tended to rely more on adult guidance and made decisions in a more cooperative way, reflecting their cultural values.

Different age groups: It would be interesting to see how older and younger children make decisions in this context.

Gender differences: It would be interesting to look at how gender might affect the way children make decisions in different cultures.

Peer influence: The study could have investigated how friends or classmates affects children's choices, especially in a social setting.

Parental roles: The study could have explored the specific roles mothers vs. fathers play in guiding children's decisions in these cultural contexts.

To explore these new factors, I would design a study that looks at how gender and parental roles influence decision-making across different cultures. Children from American and Guatemalan Mayan communities would participate in a task where they make decisions both with their mother and father involved. Additionally, the study would compare decision-making with peers in a social setting to see how much peer influence changes the choices children make, especially in different cultural contexts.

I chose Deanna Kuhn's study in 1977, and what was tested was general ideas and if two things are related. Reasoning was tested and got better with age, when compared to younger children.

The study should have included older and younger children. Also, there should have been more categories for less bias.

I would have designed the experiment to include different age groups and culturally different children also. More different children than the normal majority. It would take a little more time but would be worth it.

In the study by Miller and Kassel (1993) they focus on how children make decision and use reasoning in social contexts. They evaluate children's reasoning abilities and whether they improved or not as they age. They specifically looked at the decisions about fairness and resource allocation. The results of the study suggest that younger children will make decisions based on immediate rewards and older child were more likely to consider fairness and long-term outcomes.

The study could have used different age groups. The study focused on children ager 4-10 but it would be interesting to see the study with adolescents. The study also mainly looked at fairness and resource allocation but experiencing other variables such as social influences could offer more insight. A longitudinal study could track how children's decision-making skills develop over time. A theory-based approach using cognitive load theory or social-cognitive theory might provide a deeper understanding of how children navigate reasoning tasks.

To address these questions I would design a study with three age groups. Children would participate in decision-making tasks involving fairness, resource allocation, and social influence. The study would measure how different age groups respond to varying levels of peer pressure and different fairness criteria.

The study by Gauvain and Rogoff (1989) evaluated children's planning by looking at their route-finding abilities using essentially a supermarket route navigation task. In the study they specifically examined 5-year-olds and 9-year-old children's ability to find the most optimal route to collect items in a model supermarket but they couldn't just fly across the map. The results revealed significant differences in cognitive development where 5-year-old children created routes that were 2.6 times longer than the optimal path and performed limited map scanning, while 9-year-old children created routes only 1.5 times longer and demonstrated more thorough map examination. With that they  concluded that older children were more likely to scan and use more optimal routes suggesting that they were better at planning compared to younger children.

I think it would be helpful to focus on a broader range of ages like ages 4-12 because this range captures a critical period of cognitive development. The wider age range would provide a more significant understanding of how planning abilities progressively develop during middle childhood. Instead of a model supermarket, I'd conduct the study in an actual supermarket to test children in a real-world environment that more accurately reflects more real navigation challenges. I think it would be interesting to add time constraints to create additional cognitive load, so we could see them balance route efficiency with time management, which is a lot more complex. I would also compare neurotypical and neurodivergent children to explore how different cognitive approaches navigation and planning and I could discover strengths and weaknesses between the 2 groups.

I would do a longitudinal study that tracks children aged 4-12 in real supermarket environments. The experiment would use new technologies like eye-tracking glasses so that I could capture detailed data on navigation strategies, and I would divide participants into neurotypical and neurodivergent groups. Each participant would complete multiple trials under varying time constraints, trial 1: 15 minutes, trial 2: 10 minutes and trial 3: 5 minutes, and I would analyze route efficiency, decision-making processes and reasoning, and stress responses. The study would not only compare group differences but also create individualized cognitive mapping approaches that could share insights into diverse learning.

In Deanna Kuhn’s 1977 study explored in Topic 1: Reasoning and Decision-Making in Middle Childhood, she worked with children to evaluate their conditional reasoning. The study involved asking children aged 6 to 14 classical reasoning questions, such as “All who live in Tundor are happy. Jean lives in Tundor. Is Jean happy?” The results demonstrated a linear relationship between the ages and Modus Ponens answers (decreased as the participants' ages increased). The other results varied and did not show as clear of a pattern. 

Something that I think could have also been explored in this study is testing different age groups. For example, they could have also worked with adolescents and adults to see how conditional reasoning evolves over time, especially to observe the Modus Ponens category and determine if the relationship would continue to be linear. 

To evaluate this for people of different ages they could perform tasks that continue to follow classical reasoning but of different/higher difficulties rather than asking a 20 year old the question “All who live in Tundor are happy. Jean lives in Tundor. Is Jean happy?” they could be asked about more thought provoking scenarios. 

A study by Kuhn in 1977 evaluated conditional reasoning, in which children aged 6-14 were asked classical reasoning questions such as "All who live in Tundor are happy. Jean lives in Tundor. Is Jean happy?". The researchers aimed to observe how children evaluate logical fallacies, including modus ponens, modus tollens, affirming the consequent, and denying the antecedent. The results showed that, overall, reasoning improved with age. However, performance varied according to the format of the problem. Thus, the age does not necessary predict the amount of correct responses that they give.

Other things that the researchers could have done in the study include expanding the age range, including both children under 6 and older than 14. This could help track children's development and progression in logical reasoning. In the same way, expanding the age range into late adulthood to see if these kinds of logical reasonings decline or plateau with age or neurodegenerative disease might be interesting. Also, including participants from different backgrounds, including educational or socioeconomic, may provide information about how different environments correlate with reasoning ability.

For my study, I would examine children aged 6-14 from diverse socioeconomic backgrounds. Within each of the four grade levels, participants will be divided into three groups based on socioeconomic status: children living below the poverty line, children from middle-class families, and children from wealthy families. Each participant will be individually asked a classical reasoning question, such as "All who live in Tundor are happy. Jean lives in Tundor. Is Jean happy?". Then, I will analyze the responses not only across the four grades, but also within each socioeconomic group, focusing on logical structures such as Modus Ponens, Affirming the Consequent, Denying the Antecedent, and Modus Tollens. This design would allow for exploration into how environmental factors and social determinants may influence cognitive development and logical reasoning ability.