Students at the Center Review

Students at the Center Review

Table of Contents

Have you ever wondered how we can truly place students at the center of their learning journey? Well, let’s talk about “Students at the Center: Personalized Learning with Habits of Mind Paperback – 30 January 2017.” This book promises to not only enlighten but also empower educators to personalize the learning experience effectively. But does it deliver on this promise?

Students at the Center: Personalized Learning with Habits of Mind     Paperback – 30 January 2017

See the Students at the Center: Personalized Learning with Habits of Mind     Paperback – 30 January 2017 in detail.

The Concept of Personalized Learning

What is Personalized Learning?

Personalized learning is the hot new buzzword in education, isn’t it? It’s like the kombucha of teaching methods—everyone’s heard of it, but not everyone understands how it’s made. Personalized learning focuses on tailoring education to meet individual student needs, preferences, and interests. It’s akin to fitting a student for a bespoke suit rather than grabbing something off the rack. Think back to those times when you wished a subject could be more aligned with your interests—a little history with your love for space, perhaps? That’s the dream personalized learning aims to fulfill.

The Role of Habits of Mind

Now, let’s not overlook an essential ingredient in this educational cocktail—Habits of Mind. The authors of this book take these cognitive, affective, and behavioral habits seriously. Their idea is that these habits help students approach learning and problem-solving with a more effective mindset. It’s like teaching someone to fish rather than simply giving them fish. They learn how to learn, which is a crucial skill in today’s ever-changing world.

Students at the Center: Personalized Learning with Habits of Mind Paperback – 30 January 2017

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Unboxing “Students at the Center”

First Impressions

Picking up “Students at the Center,” our initial thought was, “It’s hefty!” But don’t let its size intimidate you. The book is well-organized and includes plenty of real-world examples, making it far from a daunting academic tome. The authors write in a way that feels like they’re having a chat with us over coffee. We found our first impression to be one of approachable wisdom.

Authors and Expertise

The authors bring a wealth of experience and credibility to the table. They’ve walked the walk in education, understanding the myriad of challenges and opportunities that come with implementing personalized learning. It’s like having a conversation with a well-read friend who also happens to know exactly what they’re talking about.

See the Students at the Center: Personalized Learning with Habits of Mind     Paperback – 30 January 2017 in detail.

Inside the Book

Structure and Content Breakdown

The book is systematically divided, ensuring that no stone is left unturned. The chapters flow logically from one to another, gradually building our understanding of personalized learning and how to implement it.

To break it down for you:

Chapter Content
Introduction Overview of personalized learning and its importance
Chapter 1 Foundations of personalized learning and habits of mind
Chapter 2 Strategic planning and goal-setting for personalized learning
Chapter 3 Practical approaches and real-world examples
Chapter 4 Integrating technology in personalized learning
Conclusion Reflecting on the journey and looking forward

Readable and relatable, each chapter is packed with actionable insights that we can start using right away.

Key Takeaways From Each Chapter

While we can’t spoil all the goodies, here are a few highlights:

Chapter 1: Foundations

We found ourselves nodding along as the authors espoused the benefits and necessity of personalized learning. They emphasize the significance of Habits of Mind in creating a culture where students can thrive. It’s almost like they knew we were skeptical but eager; they addressed common misconceptions before we even had a chance to form them.

Chapter 2: Strategic Planning

This chapter is like the battle plan before going to war, though much less intense and more about preparing rather than arming. The authors guide us through setting achievable goals and developing a strategic plan to implement personalized learning. It’s practical advice, not the usual pie-in-the-sky stuff that leaves us more confused than informed.

Chapter 3: Practical Approaches

Ah, the meat and potatoes! This chapter dives into various methods and techniques to bring personalized learning to life in the classroom. Real-world anecdotes make it incredibly relatable. We felt like we were getting tips from a seasoned mentor rather than reading a dry list of to-dos.

The Importance of Real-World Examples

Case Studies and Success Stories

Real-world examples and case studies are splashed throughout the book like sprinkles on a donut. They’re everywhere, adding flavor and value. These stories don’t just tell us what could work; they show us how it’s already working in different educational settings.

Lessons Learned

From each case study, the authors extract key lessons, making it easier for us to apply these strategies in our own environments. It’s like having the answers to the test, not just the questions.

Students at the Center: Personalized Learning with Habits of Mind     Paperback – 30 January 2017

Integration of Technology

Technology as a Tool, Not a Crutch

One of the book’s strong suits is its balanced approach to technology. It’s refreshing to see a realistic, practical view rather than a technophilic fantasyland where every problem magically disappears with the latest app. Technology is positioned as a helpful tool—not a fix-all solution. Imagine using a hammer to build a house, not to fix your dinner.

Digital Resources and Tools

The book provides a well-curated list of digital resources and tools to aid in personalized learning. It’s kind of like having an insider’s guide to the best apps and platforms that actually work. No more wandering through the app store, fingers crossed that you’ll strike gold.

Reflecting and Moving Forward

Reflective Practices for Educators

The authors stress the importance of reflection, not just for students but for educators too. They encourage us to constantly adapt and tweak our personalized learning strategies. It’s like being both the pilot and the mechanic, always ensuring the flight is going smoothly.

Looking Ahead

The book is not content with just setting us up for the now; it also looks ahead to future trends in personalized learning. This foresight helps us prepare for upcoming challenges and opportunities, ensuring we stay ahead of the curve.

Final Thoughts

Ease of Implementation

One of the book’s strengths lies in its ease of implementation. Sometimes educational theories can feel like trying to build IKEA furniture without the instructions. This book, however, is more like having a guide who not only helps assemble the furniture but also gives tips on how to use it effectively.

Personal Reflections

Reading “Students at the Center” felt like a journey. We laughed, we nodded in agreement, and at times, we had to pause to rethink our long-held beliefs about teaching and learning. The conversational tone made the complex subject matter accessible and even enjoyable.

Value for Money

Would we recommend this book to others? Absolutely. It’s a treasure trove of insights, practical advice, and real-world wisdom. For educators serious about placing students at the center of their learning experience, this book is more than worth its weight in gold.


So, where do we go from here? We take what we’ve learned, start our own personalized learning journeys, and maybe even inspire others to do the same. After all, isn’t that what being at the center is all about?

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University Student Essentials
University Student Essentials

About Me

With 25 years of experience in healthcare IT implementation, Emmanuel began his career at the University of Pittsburgh Medical Center, working as an assistant manager for a billing system implementation. Over the years, he has explored various aspects of the healthcare IT domain, successfully implementing several laboratory information systems and electronic medical record (EMR) systems, such as Cerner Millennium and Epic EMR.

In 2005, Emmanuel shifted his focus to public health, working on bio-surveillance implementation for the Centers for Disease Control and Prevention (CDC). He contributed to the BioSense Data Provisioning Project and performed extensive analysis of HL7 messages in hospitals and healthcare facilities. Additionally, Emmanuel requirements analysis for the CDC BioSense Analysis, Visualization and Reporting (AVR) project and played a key role in publishing the Situational Awareness updates to the BioSense System Requirements Specification (SRS).

Over the past 11 years, Emmanuel has worked in the Middle East, implementing the Epic EMR system at Cleveland Clinic Abu Dhabi. As a multidisciplinary team member, he has taken on various roles, including SCRUM Master, Project Manager, Integration Engineer, and Platform Engineer. Concurrently working as an adjunct university faculty member, teaching graduate-level courses in Systems Life Cycle and undergraduate courses in Health Information Systems

From a technological standpoint, Emmanuel has designed, installed, and implemented complete hospital integration systems using Rhapsody Integration Engine, MS SQL Server, and Public Health Information Networks Messaging System (PHINMS). He has also developed over 10,000 interfaces some of which coded in Java and JavaScript.

In 2019, Emmanuel expanded his skill set and entered the field of digital marketing, quickly becoming a proficient Digital Marketing Strategist. He has since helped numerous clients develop robust digital marketing strategies for their businesses. His expertise encompasses Social Media Marketing, On-page and Off-page SEO, Google Ads, and Google Analytics. Additionally, he and a team have managed clients’ website development projects, ensuring that each site is optimized for SEO, further enhancing their online presence and performance.

Alongside their digital marketing expertise, Emmanuel has delved into the world of Affiliate Marketing, where Emmanuel and his team successfully managed and executed campaigns for a variety of clients. By identifying the right products and services to promote, Emmanuel and his team helped clients generate passive income streams and increase their overall revenue.

Their approach to Affiliate Marketing involves creating valuable content that educates and engages the target audience, while strategically incorporating affiliate links. Emmanuel and his team have experience working with multiple affiliate networks and platforms, ensuring optimal tracking and reporting of performance metrics. By staying up to date with the latest trends and best practices, Emmanuel and his team have been able to optimize affiliate campaigns for maximum results, fostering long-term partnerships and sustainable growth for their clients.

As an accomplished professional, Emmanuel holds dual Bachelor of Arts degrees in Linguistics and English, a Master of Science in Health Information Systems from the University of Pittsburgh, and a Ph.D. in Information Systems from Nova Southeastern University.

My Teaching History

Professor Bazile is a dedicated technology instructor and Adjunct Faculty professor, who began his teaching career in April 2000 at the Business Career Institute in Las Vegas, Nevada.

In 2001, he expanded his expertise by training nurses in the use of Electronic Medical Records (EMR) systems. His experience in both technology and healthcare led to his appointment as an Adjunct Faculty professor at the University of Phoenix in May 2008, where he has taught several graduate-level information technology and healthcare information systems courses.

Dr. Bazile has also developed an HL7 course, which he has taught at various healthcare facilities, drawing from his own book, “HL7: Introductory and Advanced Concepts,” currently available on Amazon. With a passion for teaching and a commitment to ensuring students get the most out of each course he teaches, Dr. Bazile is a valuable asset to both his students and the institutions he serves.

My Teaching Philosophy

My teaching philosophy as an Information Systems professor in healthcare is built on the concept that education should equip students to be confident and capable problem solvers who are prepared to traverse the complicated and ever-changing landscape of Healthcare IT.

In order to accomplish this, I prioritize the creation of a dynamic and engaging learning environment that encourages students to engage with course material and with one another. This involves employing a range of teaching approaches, such as lectures, seminars, and hands-on activities, to ensure that students learn in the manner that best matches their learning style.

I believe the reason we have Information Systems as a discipline is to allow students to apply technology to solve real world problems. If that is the case, both undergraduate and graduate students have to be challenged to incorporate their core academic courses with their matriculated subjects. As such, it is important that students enter their Junior and Senior years with a strong command of the core courses such as Programming, databases, networks, hardware and software, as they serve as the foundation upon which real-world solutions will be built.

I also believe in the importance of incorporating real-world examples and case studies into my courses, as this helps to connect abstract concepts to practical applications. Additionally, I encourage students to apply what they are learning to their own personal and professional goals, as this helps to make the material more meaningful and relevant to their lives.

I strive to foster a positive and supportive learning environment where all students feel comfortable asking questions and participating in class discussions. I believe that this is key to fostering a sense of community and ensuring that all students have the opportunity to succeed.

I have also taught online courses. I have found in an asynchronous learning environment it can be difficult to apply the Peer Teaching or Experiential Learning Pedagogical Approaches. However, I have found the Discovery Learning approach to works quite well. Along with a boost to students’ self-confidence, Discovery Learning in an online environment allows students to synthesize information, expand on existing concepts on their own, while experiencing a positive outcome through trial and error.

Ultimately, my mission as an educator, and a Healthcare IT Information Systems professor is to provide students with the knowledge, skills, and confidence they need to thrive and succeed in their careers and to be technological leaders. By creating a positive and supportive learning environment, incorporating real-world examples and case studies, and encouraging students to apply what they are learning to their own objectives; my hope is to inspire and empower all students to achieve their full potential.

Population Size:

A total of 310 responses were originally received. Any response containing missing data due to unclicked radio buttons or unchecked checkboxes were first reviewed, and, if justified, were omitted from analysis. For surveys with missing data, a total of 18 responses were removed. In order to address any issues with response-set, the data was downloaded into Microsoft Access and queries ran to identify responses that contained the same values for each question. A total of 16 responses were found to be qualified for removal. Another 18 were identified as outliers and removed leaving a total of 258 responses for the study analysis.

In order to assess multivariate outliers, the Mahalanobis distances were calculated and plotted against their corresponding Chi-Square distribution percentiles (Schmidt & Hunter, 2003). The resulting scatterplot is similar to a univariate normal Q-Q plot, where deviations from a straight line show evidence of non-normality. The data showed indications of moderate deviations from multivariate normality, as indicated by the concavity of the data points. There were no additional multivariate outliers or missing values in the data after the removal of 52 responses.

Descriptive Statistics

Frequencies and percentages were conducted for the demographics indicators, while means and standard deviations were calculated for the continuous indicators. For gender, there were 151 females (59%) and 107 males (41%) in the sample. For ethnicity, most participants were Caucasian (119, 46%), followed by African American (56, 22%). The two most populous education levels were Bachelor’s (90, 35%) and Master’s (62, 22%). The biggest proportion of the sample by age group was the 35-44 age group (101, 39%) followed by the 45-54 age group (59, 23%).

Analysis:

Confirmatory Factor Analysis and Composite Reliability

A CFA was conducted along with a reliability analysis to assess construct validity. Examination of modification indices and factor loadings indicated that CSE1, CSE5, CSE7, PC5, ATE1, ATE6, ATE8, PP5, and PP6 were all causing significant problems with the model parameters. The results of the last iteration of the CFA performed in R showed significantly improved fit, although still poor overall (χ2(545) = 2125.61, p < .001, CFI = 0.82, TLI = 0.81, RMSEA = 0.11). The high degrees of freedom indicate that a very large number of parameters are being estimated in this model.

Composite Reliability

For the full model, each construct had excellent reliability. The ATE latent construct had a composite reliability value of 0.89. The ORC construct had a composite reliability value of 0.94. The CSE latent construct had a composite reliability value of 0.85 and PC had a composite reliability value of 0.95. For PP and RES, the composite reliability scores were 0.80 and 0.96 respectively. These values indicate that the loadings for each construct were all directionally similar, and that the items in each construct show a high degree of consistency.

Cronbach’s Alpha

Cronbach’s alpha values were calculated for the items in each construct. The alphas for PC (α = 0.90), AXY (α = 0.94), and RES (α = 0.94) indicated excellent reliability. The alphas for CSE (α = 0.80), ATE (α = 0.88), and PP (α = 0.83) all showed good reliability. These values confirm the results of the composite reliability tests, and reiterate the high degree of reliability within each latent construct.

Partial Least Squares – Structural Equation Modeling

A partial least squares- structural equation modeling (PLS-SEM) was conducted to determine how well the data fit the proposed model, and discern whether significant relationships existed between the independent and dependent constructs. The full model showed AVE values of 0.53 for ATE, 0.69 for AXY, 0.44 for CSE, .72 for PC, .35 for PP, and 0.81 for RES. The high values for AXY, PC, and RES indicate that the amount of variance accounted for in the manifest variables is sufficiently high. The values for ATE, CSE, and PP indicate that some of the variance in the manifest variables is left unexplained.

Structural Model

Once the measurement model had been tested for model specification, the structural model was tested to determine if ATE, AXY, CSE, PC, and PP had a significant effect on RES. A path weighted model was calculated using 10,000 bootstrap samples in R. The results showed a pseudo R-squared value of 0.78. This indicates that approximately 78% of the variance in RES is explainable by the collective effects of CSE, PC, ATE, PP, and AXY.

Further examination of the effects indicated that AXY had a highly significant effect on RES (= 0.87, < .001). This indicates that a standard deviation increase in AXY increases the expected value of RES by 0.87 standard deviations. CSE did not have a significant effect on RES (= 0.02, = .423). Additionally, CSE (= 0.02, = .423), PC (= 0.05, = .334), ATE (= 0.00, = .983), and PP (= 0.03, = .407) did not have significant effects on RES. Table 11 outlines the results of the path estimates.

Correlation Analyses

Both Pearson and Spearman correlations were calculated on the composite scores. The results of the Pearson correlations indicated that CSE was significantly correlated AXY (= 0.22, < .001) and RES (= 0.21, < .001). The results also indicated that PC was significantly correlated with ATE (= -0.79, < .001), AXY (= 0.18, < .001), and RES (= 0.20, < .001). ATE was significantly correlated with AXY (= -0.19, < .001) and RES (= -0.19, < .001). AXY was significantly correlated with RES (= 0.85, < .001).

ANCOVA Analyses

An analysis of covariance (ANCOVA) was conducted to determine if a significant relationship existed between the AXY, PP, CSE, PC, ATE scores and RES controlling for Gender, Age, Ethnicity, Education, and Specialty. The overall model was found to be significant (F(63,194) = 53.39, < .001), with an R2 value of .95, indicating that 95% of the variance in RES was explained by the collective effect of the independent variables and covariates.

Since the overall model was found to be significant, the model’s covariates were assessed. The AXY (F(10,194) = 262.20, < .001), ATE (F(7,194) = 2.20, = .036), Years computers (F(1,194) = 5.71, = .018), and PC (F(12,194) = 2.00, = .026) scores were found to be significant, indicating that a significant amount of variance in RES is explained by AXY, ATE, and PC.

A path diagram depicting the results of the structural model.

Results

This research investigated Computer Self-Efficacy (CSE), Perceived Complexity (PC), Attitudes toward EMR Systems (ATE), Peer Pressure (PP), and Anxiety (AXY) to determine whether these constructs as individuals, or as a group, or coupled together with some other factors could significantly explain resistance to EMR systems. Quantitative examination of self-reported survey results was performed to understand the strength and significance of the relationships, while these relationships were investigated to test the strength of model fit.

the regression paths of the structural model were examined to test the hypotheses. Significance was determined using an alpha level of .05. The model had an overall R2 value of 0.78. This indicates that approximately 78% of the variability in RES can be accounted for by CSE, PC, ATE, PP, and AXY. Since the overall model was significant, the individual coefficients can be interpreted. Some of the hypotheses were supported by the results of this study, and some were rejected. The construction of a data model of the relationships in this study could not meet thresholds that would be evidence of a good fit of the relationships identified in the study.

The fifth hypotheses tested the influence of AXY on resistance to EMR systems. AXY was expressed to be significantly related to resistance (r=.87, p<.001). This finding supports the hypothesis that anxiety with the EMR system will lead to medical care professionals rejecting use of the system. Unlike the findings of the first four hypotheses, the findings of the current study support previous research. Angst and Agarwal (2009) indicated that AXY is a factor which is significantly related to the problem of EMR system resistance. Based on the empirical findings of previous research, the present research and conceptual propositions and conclusions in previously written scholarly articles, there is a great deal of support for the finding that AXY is significantly influenced by EMR resistance.

The findings of this research do not support all findings by previous researchers, and there are multiple relationships which had been established as being significant that were identified as being insignificant in the current research. Generally, because of the inconsistency of previous findings and the current study there may be elements related to the sample examined or other contextual factors which may contribute to the inconsistency that exists. Ultimately, it is suggested that there be further research done on the problem of resistance to EMR system use.

Ultimately the findings support a new take on the problem of EMR system resistance that may contribute to the ways in which scholars investigate the problem of EMR resistance in general. This may also help with the way practitioners approach EMR systems, and articulate value of the systems to medical professionals investing record-keeping systems in the workplace.