MODULE 2 ASSIGNMENT

MODULE 2 ASSIGNMENT

Student’s Name

Institutional Affiliation

Professor

Date of Submission

MODULE 2 ASSIGNMENT

Current Evidence Concerning the Use of Learning Style Inventories and How to Use Such Tools

Empirical evidence clearly shows that there is currently not enough evidence to justify the use of learning style inventories (Newton & Miah, 2017). According to Bhagat et al. (2015), even though learning style inventories are renowned classroom tools, researchers have established little evidence to support that matching the learning preference of a student to the instructional strategy results in improved educational outcomes. The authors further reveal that several scholars have found that learners who are taught according to their preferred learning style do not perform better than those who are unmatched with their learning style.

Learning style inventories are in the form of questionnaires and are mostly utilized in the classroom to help respondents identify their preferred learning style. Supporting this statement, Çakıroğlu (2014) reveals that learners have differing preferences for how they learn new information. As such, I would use learning style inventories at the beginning of a class to learn more about my students’ needs. Since no single tool can be used to measure all domains of learning: psychomotor, cognitive, and affective, I can combine two or more learning style inventories to understand my student’s needs and their preferred learning. Understanding my student’ preferred learning styles will allow me to develop a teaching approach that will incorporate all their learning needs.

Types of Diverse Students and How to Meet Their Learning Needs

One type of diverse student population is auditory learners. This group of students learns by hearing and listening. Auditory learners remember content with ease when it is presented in an auditory format (Rogowsky et al., 2020). Usually, these learners should be introduced to new information by first hearing about it and then providing verbal feedback to reinforce it (Bastable, 2019). Therefore, to meet this group of students’ learning needs, I can record class content and share it with students before the actual class meeting. I can request the students to listen to the audio before we meet for the next class. Allowing the students to listen to the audio and explaining to them the audio content will help meet their learning needs. Also, since these students learn by hearing and listening, I can adopt group discussions as a teaching approach. I can also minimize noise during the class to meet the learning needs of auditory learners.

Visual learners are another type of diverse student population. Instead of words, these students mostly utilize visual imagery, colors, graphics, symbols, and pictures to learn. Usually, visual students must see the information so as to learn it (Rogowsky et al., 2020). Furthermore, visual learners have a photographic memory and may use tone, color, and brightness to recall information. To meet visual students’ learning needs, I can use relevant pictures, charts, and graphs while using projectors to oblige the course content to enhance students’ understanding. Since these students can use color and brightness to recall information, I can also use shading codes and signal to help them remember the content taught. Since Bastable (2019) urges that visual students learn more easily by observing, viewing, and watching, I can ensure that I use demonstrations so as to meet their learning needs.

Another type of diverse student population is tactile learners. This group of learners learns through handling, touching, and manipulating objects (Buşan, 2014). According to Bastable (2019), tactile learners remember when they draw, write, and move their fingers. Therefore, to meet these students’ learning needs, I can empower them to recopy notes during the study time. I can also adopt the use of scientific experiments when teaching this group of students so as to ensure that their fingers are engaged.

Strategies that Affect Students’ Readiness to Learn and Strategies that Can be Implemented Across All Adult Learner Populations.

Students’ readiness to learn can be affected by several factors. To begin with, anxiety level significantly impacts students’ emotional readiness to learn. Anxiety influence’s student’s ability t perform at the psychomotor, cognitive, and affective levels. Fear, a significant contributor to anxiety, adversely affects learners’ readiness to learn in the three learning domains. Different levels of anxiety affect students’ readiness to learn differently. Low anxiety levels may lead to inaction on the part of the student, while a moderate level of anxiety motivates students to learn. As the anxiety level increases, the learner’s emotional readiness to learn starts to increase and starts to decline after reaching a peak (Bastable, 2019). A strategy that can be implemented across all adult learner populations to increase motivation to learn includes ensuring that the learner’s anxiety level is moderate and less emotional. Anxiety levels can be moderated by engaging in physical exercise since it allows the learner to stay active.

Health status also affects a learner’s physical readiness to learn. The student’s health status is crucial for determining the amount of energy available and the learner’s comfort level, influencing their readiness to learn. Energy-reducing demands which result from the body’s response to diseases and illnesses require the student to spend large amounts of psychic and physical energy, thus leaving little energy for actual learning. Consequently, this reduces the student’s readiness to learn. On the other hand, healthy learners have high amounts of energy available for learning, increasing their readiness to learn. A strategy that can be implemented across all adult learner populations to increase motivation to learn includes promoting health-living behaviors such as healthy eating and engaging in physical exercise (Bastable, 2019).

Furthermore, environmental effects also affect a student’s readiness to learn. An environment conducive to learning helps maintain the student’s attention and stimulate their interest in learning. On the other hand, unfavorable environmental conditions adversely affect students’ learning readiness. For instance, very high levels of noise induce vibration of body parts which negatively affects levels of concentration. A strategy that can be implemented across all adult learner populations to increase motivation to learn to include creating a favorable learning environment free from noise and other distractions (Bastable, 2019).

Also, the complexity of tasks affects students’ readiness to learn. Variations in the complexity of a task affect the degree to which behavioral changes are necessary for the psychomotor, cognitive, and affective domains (Bastable, 2019). For example, it is difficult for a student who has learned a psychomotor skill for completing a certain task to learn a new skill if the procedural steps of undertaking that task change. This is because learning new skills and unlearning the past steps increases the complexity of the task. Therefore, a strategy that can be implemented across all adult learner populations to increase motivation to learn entails providing training classes before the change is introduced.

How American with Disability Act (ADA) Affects Learning and Teaching in Higher Education and How to Meet the Needs of Students with Special ADA Needs

The ADA was signed into law on July 26, 1990 by President George H. W. Bush. ADA protects individuals living with disability from discrimination (Bastable, 2019). The ADA affects learning and teaching in higher education in different ways. Firstly, the ADA mandates that higher education institutions should make fair provisions for disabled students (Vance et al., 2014). It requires that higher education institutes that receive federal funding must not discriminate in student care, recruitment, and admission. Also, the ADA provides that students with disabilities can ask for academic accommodations, which may include auxiliary aids, to enable them to enroll and learn from all postsecondary educational activities and programs. This provision ensures that all institutions of higher learning make adjustments to ensure that the academic program is accessible to students with disabilities. The ADA also assists in implementing necessary changes in laws, processes, and procedures and facilitates the accessibility of classes and exams, which are crucial in making sufficient arrangements for disabled students.

To meet the needs of a learner with special ADA needs, several strategies can be incorporated into the teaching/learning plans. First, a universal design and provision of accommodation are the main strategies for increasing the overall accessibility of higher education by disabled students. Secondly, the use of technology in institutions of higher learning can help meet the needs of a student with special ADA needs. For example, technology can be used to facilitate online learning. Notably, online learning may be more suitable for students with physical disabilities than physical classes. Also, adopting technology can be beneficial for creating a favorable experience in institutions of higher education. For instance, assistive technology can be used to deal with print-related disorders by enlarging the text or helping deaf and hard-of-hearing students with hearing aids. Since such technologies may take longer to master, they can be accompanied by sufficient training for both instructors and teachers. Another strategy that can be incorporated in teaching/learning plans to meet the needs of a student with special ADA needs is the introduction of peer to peer mentoring programs as well as academic coaching to help other students understand the needs of the students with disability and learn how they can help them. Higher education institutions can also expand mobility for wheelchairs in restrooms and introduction of door handles and hard products. Also, lifts should be introduced in institutions for higher learning to make movement easy for students with special ADA needs.

References

Bastable, S. B. (2019). Nurse as an educator, principles of teaching and learning practice.

Bhagat, A., Vyas, R., & Singh, T. (2015). Students awareness of learning styles and their perceptions to a mixed-method approach for learning. International Journal of Applied and Basic Medical Research, 5(Suppl 1), S58. https://dx.doi.org/10.4103%2F2229-516X.162281Buşan, A. M. (2014). Learning styles of medical students-implications in education. Current health sciences journal, 40(2), 104. https://dx.doi.org/10.12865%2FCHSJ.40.02.04Çakıroğlu, Ü. (2014). Analyzing the effect of learning styles and study habits of distance learners on learning performances: A case of an introductory programming course. International Review of Research in Open and Distributed Learning, 15(4), 161-185. https://doi.org/10.19173/irrodl.v15i4.1840Newton, P. M., & Miah, M. (2017). Evidence-based higher education–is the learning styles ‘myth important?. Frontiers in psychology, 8, 444. https://dx.doi.org/10.3389%2Ffpsyg.2017.00444Rogowsky, B. A., Calhoun, B. M., & Tallal, P. (2020). Providing instruction based on students’ learning style preferences does not improve learning. Frontiers in Psychology, 164. https://doi.org/10.3389/fpsyg.2020.00164Rogowsky, B. A., Calhoun, B. M., & Tallal, P. (2020). Providing instruction based on students’ learning style preferences does not improve learning. Frontiers in Psychology, 164. https://doi.org/10.3389/fpsyg.2020.00164Vance, M. L., Lipsitz, N. E., & Parks, K. (2014). Beyond the Americans with Disabilities Act: Inclusive Policy and Practice for Higher Education. NASPA-Student Affairs Administrators in Higher Education. 1875 Connecticut Avenue NW Suite 418, Washington, DC 20009.

Module 2 Assignment

Scenario

Smart businesses in all industries use data to provide an intuitive analysis of how they can get a competitive advantage. The real estate industry heavily uses linear regression to estimate home prices, as cost of housing is currently the largest expense for most families. Additionally, in order to help new homeowners and home sellers with important decisions, real estate professionals need to go beyond showing property inventory. They need to be well versed in the relationship between price, square footage, build year, location, and so many other factors that can help predict the business environment and provide the best advice to their clients.

Prompt

You have been recently hired as a junior analyst by D.M. Pan Real Estate Company. The sales team has tasked you with preparing a report that examines the relationship between the selling price of properties and their size in square feet. You have been provided with a Real Estate Data Spreadsheet spreadsheet that includes properties sold nationwide in recent years. The team has asked you to select a region, complete an initial analysis, and provide the report to the team.

Note: In the report you prepare for the sales team, the response variable (y) should be the listing price and the predictor variable (x) should be the square feet.

Specifically you must address the following rubric criteria, using the Module Two Assignment Template:

  • Generate a Representative Sample of the Data
  • Analyze Your Sample
  • Generate Scatterplot
  • Observe patterns

You can use the following tutorial that is specifically about this assignment. Make sure to check the assignment prompt for specific numbers used for national statistics and/or square footage. The video may use different national statistics or solve for different square footage values.

What to Submit

Submit your completed Module Two Assignment Template as a Word document that includes your response, supporting charts, and Excel file.

Module 2 Assignment

Senario:

Smart businesses in all industries use data to provide an intuitive analysis of how they can get a competitive advantage. The real estate industry heavily uses linear regression to estimate home prices, as cost of housing is currently the largest expense for most families. Additionally, in order to help new homeowners and home sellers with important decisions, real estate professionals need to go beyond showing property inventory. They need to be well versed in the relationship between price, square footage, build year, location, and so many other factors that can help predict the business environment and provide the best advice to their clients.

Prompt

You have been recently hired as a junior analyst by D.M. Pan Real Estate Company. The sales team has tasked you with preparing a report that examines the relationship between the selling price of properties and their size in square feet. You have been provided with a Real Estate Data Spreadsheet spreadsheet that includes properties sold nationwide in recent years. The team has asked you to select a region, complete an initial analysis, and provide the report to the team.

Note: In the report you prepare for the sales team, the response variable (y) should be the listing price and the predictor variable (x) should be the square feet.

Specifically you must address the following rubric criteria, using the Module Two Assignment Template:

  • Generate a Representative Sample of the Data
  • Analyze Your Sample
  • Generate Scatterplot
  • Observe patterns

You can use the following tutorial that is specifically about this assignment. Make sure to check the assignment prompt for specific numbers used for national statistics and/or square footage. The video may use different national statistics or solve for different square footage values.

0 replies

Leave a Reply

Want to join the discussion?
Feel free to contribute!

Leave a Reply