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R Programming Assignment Help in Australia

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Empower Your Career with Digicrome Academy's Comprehensive Data Science and AI Training

Discover the power of data with Digicrome Academy’s comprehensive training in Data Science and AI. Our cutting-edge curriculum and state-of-the-art tools will prepare you for a career at the forefront of technology. With industry-recognized certification and personalized mentorship, you’ll be well-equipped to tackle any data challenge. Join Digicrome Academy today and start your journey to success.

Table of contents

what is Digicrome Academy?

Objective of Digicrome

What do we offer?

Leading Trainers paving the way to Success

What do our Learners say?

Benefits at Digicrome Academy

Six types of Certification

What Learners will gain?

What is Digicrome Academy?

Digicrome Academy is an online learning platform that offers a range of certifications in areas such as data science, AI, machine learning, and deep learning. These certifications are designed to help individuals develop the skills and knowledge needed to succeed in today’s digital economy. Additionally, the academy aims to be flexible and accessible, allowing learners to balance their studies with their work and personal commitments.

Digicrome is Asia’s leading brand that provides online Data Science and Artificial Intelligence Courses in 60+ countries like Australia, Canada, USA, Singapore, India, etc. We provide complete practical training with a 100% Job Placement Guarantee.

Objective of Digicrome

Digicrome was founded in the year of 2013 as an E-Learning Provider. Since its inception till date, the founders, Mr. Parichit Bhamri & Mr.Ranbir Rawal have aimed to grow the academy as an emerging academy that has always transformed lives. We also aim to deliver employment to at least 2K students each year we grow.

With more than 10K+ registered learners, Digicrome has partnered with over 200+ leading companies to offer handsome jobs to our learners.

What do we offer?

Digicrome Academy offers an 11-month PG Certification Program in Data Science & Artificial Intelligence. After 11 months, along with a course completion certificate, the academy provides 6 other certificates to the learners. Let’s have a look at the points:

· 11-Month Online Program with Live Mentorship on weekends

· 3-Month paid Internship under Personal Mentorship of assigned Data Scientist

· 100% Placement guarantee*

· Dedicated Placement Team and Support

· Dedicated Interview preparation batch

· Industrial-level projects and interview preparation for those projects dedicated to mock interviews.

· 25+ Industry Graded projects to give you maximum practical exposure.

As Data Science & AI is all about practising with tools, Digicrome academy offers its learners the to learn with Google Data Studio, My SQL, Power BI, Tableau, and others.

Leading Trainers paving the way to Success

The Trainers of Digicrome Academy are well versed in the course, who not only provide training but also mentor the students for a bright career. Our trainers have a strong foundation in statistics, machine learning algorithms, data visualization techniques, and programming languages such as Python or R. Our trainers are passionate about sharing their knowledge and helping others learn. They enjoy teaching and are patient, understanding, and empathetic toward their students.

What do our Learners say?

Many students who have taken data science courses from Digicrome have reported that they found the courses to be very valuable in terms of the knowledge and skills they gained. Some students have reported that the courses were challenging, but also rewarding, as they were able to apply the concepts and techniques they learned to real-world problems and projects. Students have also reported that they appreciated the hands-on and practical approach of many data science courses, which allowed them to develop their skills through real-world projects and case studies. They have also found the instructors and mentors to be knowledgeable and supportive, providing guidance and feedback throughout the learning process.

Overall, students who have taken data science courses from Digicrome Academy have reported that they gained a deeper understanding of data science concepts, learned new skills and techniques, and were able to apply these skills to solve real-world problems. They have also reported that the courses helped them to advance their careers and become more competitive in the job market.

Benefits at Digicrome Academy

1. Learning Management System (LMS) — A software application designed to manage and deliver online learning materials, track student progress, and provide various tools for course management. Learners can get access to the course they have enrolled in and can preview it. In the Live Virtual Class, they can find all the important details about the live session and can also get access to recorded classes.

2. Access to Industry Experts — Digicrome Academy provides students with access to industry experts through guest lectures, networking events, and other opportunities. This allows students to gain valuable insights into the field and make connections with professionals in the industry.

3. Hands-on Experience — The course is designed to provide students with hands-on experience in data science and AI through real-world projects, case studies, and simulations. This helps students gain practical experience and develop a deeper understanding of the concept.

4. Flexible Learning Options — The course is designed to accommodate students with different learning styles and schedules. Students can choose to attend live online classes, study at their own pace through self-paced learning, or attend in-person classes.

5. Industry Relevant Curriculum — The curriculum of the Data Science and AI course is constantly updated to keep pace with the latest advancements in the field. The course covers the most in-demand tools and techniques used by data scientists and AI professionals, ensuring that students are equipped with the skills that are relevant to the industry.

6. Highest Paid Salary — Data Science & AI now boasts to be picking up the highest paid salary in the country after other hierarchy positions. A fresher in data science can be offered with a maximum of 7 LPA to 10 LPA.

Six types of Certification

After the completion of 11 Months of training, you will get 7 certificates in total.

1) Course completion certificate for PGP in Data Science

2) Data Science — Machine Learning

3) Data Science — Deep Learning

4) Data Science — Artificial intelligence

5) Data Science — Python

6) Data Science — NLP

7) 3 Months Internship certificate with one of our partner organisations

Certificates hold a significant advantage in the job market and can provide you with various benefits such as:

Recognition: Certificates are a validation of your skills and knowledge in a particular field. They add credibility to your resume and showcase your expertise in the subject matter.

Career Advancement: Having certificates can help you advance in your career as they demonstrate that you have invested time and effort in developing your skills. They can also make you a more competitive candidate for promotions and new job opportunities.

Salary Increase: Certificates can also increase your earning potential. Employers often offer higher salaries to employees who possess additional certifications as it indicates that they have a higher level of knowledge and expertise.

Networking Opportunities: Obtaining certificates can help you connect with others in your field and provide you with networking opportunities. You can attend conferences, webinars, and other events related to your field, which can help you build connections and expand your knowledge.

Overall, obtaining certificates can be a valuable investment in your career and can help you stand out in the job market.

What Learners will gain?

After you complete your program, you will:

1) Be well versed in analytics tools and technologies such as Python, Tableau, and My SQL

2) Apply industry-relevant machine learning techniques such as Regression, Predictive Modeling, Clustering, Time Series, Forecasting, Classification, NLP, etc.

3) Structure a business problem into an analytics framework using statistics and data modeling

4) Be well versed in Deep Learning, Natural Language Processing (NLP)

5) Present yourself as an ideal candidate for Data Analyst, Data Scientist, or Business Analyst roles within leading analytics

6) Pre-Placement Activities like:

.Resume Building Sessions

.LinkedIn Optimization Sessions

.Interview Skills Sessions

.Topic Wise Interview Questions & Answers Discussion

.HR Mock Interviews

.Technical Mock Interviews

.Soft skill preparation

In the coming years, we are likely to see data scientists using AI and ML technologies to automate some of the repetitive and time-consuming tasks involved in data analysis, such as data cleaning and pre-processing. This will allow data scientists to focus on more strategic tasks, such as developing new models, testing hypotheses, and generating insights.

Overall, data science is likely to remain a crucial career choice, as the demand for professionals with a strong foundation in data analysis and machine learning continues to grow across industries. Thus, Digicrome Academy aims to fulfil the dreams of those who aspire to become one.

About the Author

Meet Aayush, a Senior Research Analyst at Digicrome with a passion for exploring the world of Data Analytics, Artificial intelligence, Machine Learning, and Deep Learning. With his insatiable curiosity and desire to learn, Aayush is always looking for ways to expand his knowledge and skills in the field.

For Data Science course & certification related queries visit our website:- www.digicrome.com & you can also call our Support:- 0120 311 3765

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After-school Tutoring Market is Booming Worldwide | EF Education First, iTutorGroup, Scholars Education, ZhugeAacademy

Advance Market Analytics published a new research publication on “Global After-school Tutoring Market Insights, to 2027” with 232 pages and enriched with self-explained Tables and charts in presentable format. In the study, you will find new evolving Trends, Drivers, Restraints, Opportunities generated by targeting market-associated stakeholders. The growth of the After-school Tutoring market was mainly driven by the increasing R&D spending across the world.

Major players profiled in the study are:

China Distance Education Holdings Ltd (China), EF Education First Ltd (Switzerland), ChineseHour (China),  Koolearn Technology Holding Ltd (China), New Oriental Education and Technology Group Inc. (China), TAL Education Group (China), Blackboard, Inc. (United States), BYJU’S (India), Scholars Education (Canada), iTutorGroup (United States), ZhugeAacademy (Canada)

Get Exclusive PDF Sample Copy of This Research @ https://www.advancemarketanalytics.com/sample-report/38494-global-after-school-tutoring-market#utm_source=DigitalJournalVinay

Scope of the Report of After-school Tutoring

After school tutoring might help students perceive learning in a different perspective. Students can associate schooling with positive thoughts by working in a comfortable location with personal items (preferred toy, pet, etc.) close at hand. Learning becomes a breeze when this happened! A tutor makes it a priority to form positive relationships with learners, and the one-on-one setting aids in this effort. When a student creates a strong bond with a teacher, learning becomes a pleasurable experience. School suddenly becomes less difficult, and the self-esteem soars! Students’ grades will naturally increase as they continue via after-school tutoring. Student also start to improve in areas where teachers don’t usually assign grades. After-school tutoring will teach students life skills such as organization, work ethic, critical thinking, problem solving, and time management.

On 24 October 2021 EduTech startup HomeSkul has launched the first home-grown afterschool e-learning app which provides AI and Augmented Reality (AR) -powered personalised learning experience for students

The Global After-school Tutoring Market segments and Market Data Break Down are illuminated below:

by Type (Private in-home sessions, Free “drop-in” tutoring, Paid sessions at established organizations, Intensive specialized sessions, Online tutoring), Tutoring Programs (English Tutoring, French Tutoring, Advanced Function Tutoring, Physics Tutoring, Biology tutoring, Other), School (Primary School, Secondary School), End Use (Professor, Teacher, Student)

Market Opportunities:

Increasing Number Of Specialized Tutoring Class In Develop Region

Government Favorable Incentive Of Developing Public School

Market Drivers:

Rapidly Urbanization And Rising Funding In Education Sector

Market Trend:

Growing Adoption Of Cloud Base Technology In School

What can be explored with the After-school Tutoring Market Study?

Gain Market Understanding

Identify Growth Opportunities

Analyze and Measure the Global After-school Tutoring Market by Identifying Investment across various Industry Verticals

Understand the Trends that will drive Future Changes in After-school Tutoring

Understand the Competitive Scenarios

Track Right Markets

Identify the Right Verticals

Region Included are: North America, Europe, Asia Pacific, Oceania, South America, Middle East & Africa

Country Level Break-Up: United States, Canada, Mexico, Brazil, Argentina, Colombia, Chile, South Africa, Nigeria, Tunisia, Morocco, Germany, United Kingdom (UK), the Netherlands, Spain, Italy, Belgium, Austria, Turkey, Russia, France, Poland, Israel, United Arab Emirates, Qatar, Saudi Arabia, China, Japan, Taiwan, South Korea, Singapore, India, Australia and New Zealand etc.

Have Any Questions Regarding Global After-school Tutoring Market Report, Ask Our Experts@ https://www.advancemarketanalytics.com/enquiry-before-buy/38494-global-after-school-tutoring-market#utm_source=DigitalJournalVinay

Strategic Points Covered in Table of Content of Global After-school Tutoring Market:

Chapter 1: Introduction, market driving force product Objective of Study and Research Scope the After-school Tutoring market

Chapter 2: Exclusive Summary – the basic information of the After-school Tutoring Market.

Chapter 3: Displaying the Market Dynamics- Drivers, Trends and Challenges & Opportunities of the After-school Tutoring

Chapter 4: Presenting the After-school Tutoring Market Factor Analysis, Porters Five Forces, Supply/Value Chain, PESTEL analysis, Market Entropy, Patent/Trademark Analysis.

Chapter 5: Displaying the by Type, End User and Region/Country 2016-2021

Chapter 6: Evaluating the leading manufacturers of the After-school Tutoring market which consists of its Competitive Landscape, Peer Group Analysis, BCG Matrix & Company Profile

Chapter 7: To evaluate the market by segments, by countries and by Manufacturers/Company with revenue share and sales by key countries in these various regions (2022-2027)

Chapter 8 & 9: Displaying the Appendix, Methodology and Data Source

Finally, After-school Tutoring Market is a valuable source of guidance for individuals and companies.

Read Detailed Index of full Research Study at @ https://www.advancemarketanalytics.com/buy-now?format=1&report=38494#utm_source=DigitalJournalVinay

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Syllabus, Social Media and Society, 2018

Sharing is caring. I found other people’s syllabi very helpful when designing my two new courses - Social Media and Society and Digital Culture. Both are masters’ level, both will be taught at Tallinn University in the New Media Masters program this fall. I am still working on the details of Digital Culture, but here’s Social Media and Society:

Social Media and Society, 4ETC

taught by: Katrin Tiidenberg, PhD

Short description: ‘Social Media and Society’ considers the role of networked communication technologies, social media, and specific platforms and applications in personal and societal life. It takes a sociological perspective on society (conceptualized via structure, agency, social institutions, inequality, social change and knowledges) and makes sense of social media via the concepts of affordances, platforms, connectivity, (in)visibility and user practices. Relying on relevant academic work that conceptualizes the social dynamics and implications of social media, we will explore the personal, social, economical, political and ideological aspects of living in networked, digitally saturated societies.

Course structure:

Lectures

In-class discussions

3 in-class exit quizzes (about the content of the class)

6 in-class reading quizzes (about the reading assigned for that class).

Participation in and passing the class involves reading a total of 13 texts (journal article or book chapter length) in academic English.

Grading:

Grades are based on the total number of accumulated points (100p = 100%). Points are earned from in-class quizzes (reading or class content related) and from the written exam. Maximum possible points: 45  - quizzes (5 per quiz), 55 – final exam.

A -  100% - 91%

B – 90% - 81%

C – 80% - 71%

D – 70% - 61

E – 60% - 51

F – 50% and less

Sept 6 - Intro & TRUTHS AND KNOWLEDGES

16:15 – 17:45

Introduction to the course, introduction to social media and society.

What is social media? What are its social implications?

How do we make sense of society?

What are the main concepts we use to study networked society and mediated sociality?

18:15 – 19:45

Truth, knowledge and discourse.

Attention, polarization and the public sphere.

News and information. Truth, post-truth, fake news, deep fakes. Flop accounts.

Augmented reality.

Exit quiz

*

Sept 13 - STRUCTURE AND AGENCY

16:15 – 17:45

Structure as Governance  -  governments and corporations, social institutions, platforms

Structure as Infrastructures – networks, databases, datafication, automation

Structure as Maintenance – algorithms, affordances, automation, bots, content moderation.

Failures and Breakdowns.

Read: Gillespie, T. (2017). Governance of and by platforms. In Sage Handbook of Social Media.

Reading quiz

18:15 – 19:45

Agency and self-presentation: Identity and networked communication technology, identification, self- and group categorization, interaction on and with social media, social cues, self-presentation, automated / datafied representations of the self, qualified self.

Read: Humphreys, L. (2018). Qualified Self, the Introduction.

Reading quiz

*

Sept 20 - Visibility, power and social inequalities. Categorization and identification

16:15 – 17:45

Visibility and invisibility on social media: Privacy, anonymity, pseudonymity, privilege, boundary work, shaming, moral panics

Read: Marwick, A., Fontaine, C., & Boyd, D. (2017). “Nobody Sees It, Nobody Gets Mad”: Social Media, Privacy, and Personal Responsibility Among Low-SES Youth. Social Media + Society, 3(2), 1–14.

Reading quiz

18:15 – 19:45

Visibility and invisibility via social media: surveillance, power, algorithms, social sorting

Read: Brayne, S. (2017). Big Data Surveillance: The Case of Policing. American Sociological Review. 1-32.

Reading quiz

*

Sept 27 - Social Institutions and networked capitalism                

16:15 – 17:45

Labor, work and exploitation: immaterial labor, aspirational labor, venture labor, glamor labor, visibility labor. If it seems free, you’re the product.

“Sharing” economies, platformisation and appification of labor.

Read: Duffy, B. E. (2016). The romance of work: Gender and aspirational labour in the digital culture industries. International Journal of Cultural Studies, 19(4), 441–457.

Reading quiz

18:15  - 19:45

Consumer culture and networked capitalism: personalization, advertising, commodification (of data and attention), self-branding

Exit quiz

*

Oct 4

Future Making

16:15 – 17:45

Civic engagement, political participation, activism, social justice.

Publics (networked, affective, ad hoc).

Read: Poell, T., & van Dijck, J. F. T. M. (2018). Social media and new protest movements. In The SAGE Handbook of Social Media.

Reading quiz

18:15 – 19:45

Net Neutrality, Critical Literacy, alternative Social media

Exit quiz

*

Oct 11

Reading week

Read the 6 additional pieces for the exam.

Oct 18

EXAM

**

Readings for exam:

Bucher, T & Helmond, A. (2017). The affordances of social media platforms. The SAGE Handbook of Social Media, edited by Jean Burgess, Alice Marwick, and Thomas Poell. 223-253

Casilli, A. (2015). Four Theses on Digital Mass Surveillance and the Negotiation Of Privacy. 8th Annual Privacy Law Scholar Congress 2015, Jun 2015, Berkeley, United States. 2015.

Gehl, R. W. Alternative Social Media : From Critique to Code, 1–23. The SAGE Handbook of Social Media, edited by Jean Burgess, Alice Marwick, and Thomas Poell.

Humprecht, E. (2018) Where ‘fake news’ flourishes: a comparison across four Western democracies, Information, Communication & Society.

Marwick, A. (2016). “ What Can I Really Do ?” Explaining the Privacy Paradox with Online Apathy, 10, 3737–3757.

Van Dijck, José. 2014. Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & Society 12(2): 197-208.

***

Suggested readings for those interested in these topics, or contemplating a related MA thesis:

Books

Tarleton Gillespie, Custodians of the Internet, 2018

Akane Kanai, Gender and Relatability in Digital Culture, Managing Affect, Intimacy and Value, 2018

Siva Vaidhyanathan, Antisocial media, how Facebook disconnects us and undermines democracy, 2018

Safiya Noble, Algorithms of Oppression: How Search Engines Reinforce Racism, 2018

If you read Estonian:  Katrin Tiidenberg, Ihu ja Hingega internetis: kuidas mõista sotsiaalmeediat, 2017.

Socialbots and their friends, Digital media and the automation of sociality, edited by Roberg W. Gehl and Maria Bakardjieva, 2016.

Digital Sociologies, edited by Jessie Daniels, Tressie McMillan Cottom, Karen  Gregory, 2016

Nancy Baym, Personal Connections, 2015

Jose van Dijck, Culture of Connectivity, 2013

Articles / chapters

Markham, A. N. (forthcoming). Critical pedagogy as a response to datafication: Research methods as data literacy tools. Qualitative Inquiry. (title may change). Final draft here:  https://www.dropbox.com/s/suf2uoesim4slkl/critical_pedagogy_as_data_literacy_final_draft_feb_2018.pdf?dl=0

Gerrard, Y. (2018) Beyond the hashtag: Circumventing content moderation on social media. New Media and Society. ISSN 1461-4448

Stevenson, M. (2018). From hypertext to hype and back again: exploring the roots of social media in the early web. In J. Burgess, A Marwick and T Poell (eds.). The SAGE Handbook of Social Media. Sage Press.

van der Nagel, E. (2018). “Networks that work too well”: intervening in algorithmic connections. Media International Australia, 168(1), 81–92.

Duffy, B. E., Pruchniewska, U., & Scolere, L. (2017). Platform-specific self-branding: Imagined affordances of the social media ecology. 8th International Conference on Social Media & Society, 1–9. http://doi.org/10.1145/3097286.3097291

Marwick, A. and Lewis, R. (2017). Media Manipulation and Disinformation Online. Data and Society. Retrieved from https://datasociety.net/output/media- manipulation-and-disinfo-online/

Papacharissi, Z. (2016). On networked publics and private spheres in social media. In Hunsinger, J. and Senft, T. The Social Media Handbook. New York: Routledge.

Abidin, C. (2016). “Aren’t These Just Young , Rich Women Doing Vain Things Online?”: Influencer Selfies as Subversive Frivolity. Social Media + Society, 1–17. http://doi.org/10.1177/2056305116641342

Marwick, A. E. (2015). Instafame: Luxury Selfies in the Attention Economy. Public Culture, 27(1 75), 137–160. http://doi.org/10.1215/08992363-2798379

Ross, A. (2013). In search of the lost paycheck. In T. Scholz, Digital labor: The Internet as playground and factory. (13-32). New York: Routledge

cf. Annette Markham's Future Making Project - https://futuremaking.space/

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Nakia Levi Readerly Exploration #1

Due Date: September 14, 2018 

Titles of Readings: “Toward an educationally relevant theory of literacy learning: Twenty years of inquiry” by Brian Cambourne, and “Building a Literacy Community: The Role of Literacy and Social Practice in Early Childhood Programs” by Susan J. Britsch and Daniel R. Meier

Cambourne’s main takeaway: Certain conditions that promote oral language acquisition can be adapted into the literacy classroom to similarly prompt literacy learning.  At the heart of these conditions lies student engagement, which is the essential component to literacy success.

Cambourne nugget: “How could a brain which could master such complex learning in the world outside school be considered deficient with respect to the kinds of learning that were supposed to occur inside the school?” (Cambourne, 1995, p.183).  I found this quote and discussion surrounding Cambourne’s statement fascinating, as he related this disconnect in learning to the way in which things are taught in different “settings.”

Britsch and Meier’s main takeaway: Literacy learning must involve active student participation.  It is important for teachers to stray away from rigid instruction and strive to make literacy a creative and proactive process for students to achieve ownership of learning.

Britsch and Meier nugget: “…literacy becomes more than simply encoding and decoding print on the page; it makes literacy into a ‘life world’ where children matter” (Britisch & Meier, 1999, p.214).  This quote that concludes the article was really a game changer, as it encompasses the whole purpose of the text.  It helped me to rethink the goal of literacy instruction and refocus it from an inward understanding to an outward expression of understanding, where thoughts and insights are shared within the class community for the benefit of all students.

Pre-reading author research:

About the author of “Toward an educationally . . .”

Brian Cambourne: “He has since become one of Australia’s most eminent researchers of literacy and learning . . . Brian devoted his research to literacy learning and teaching. His major interest is in professional development for literacy education and he is committed to the idea of co-learning and co-researching with teachers” (Cambourne, n.d.).  

Having no prior background knowledge of Cambourne and his work, I quickly realized that he is highly recognized in education for his literacy research.  Gaining this insight before reading his article allowed me to appreciate its credibility, and it also built excitement and anticipation to learn his perceptions and conclusions regarding teaching and learning literacy in the classroom. 

About the authors of “Building a Literacy Community. . .”

Susan J. Britsch: Britsch is a professor of Curriculum and Instruction in the College of Education at Purdue University and has done a significant amount of research, including, but not limited to the topics of English Language Learning and visual literacy.  She has several publications surrounding these topics, and more!  In addition, many of her project focus on literacy in some way (Purdue University, n.d.).  From this information, it is evident that Britsch is well qualified and educated in the area of literacy, which results in a very relevant text.

Daniel R. Meier: Dr. Meier is an Elementary Education professor at San Francisco State University and “[h]is research interests are in young children's multilingual and literacy development, narrative and memoir, early childhood international education, and teacher research and inquiry” (San Francisco State University, n.d.). 

It is helpful to have this context and biographical knowledge about Dr. Meier as it allowed me to see the personal connection between his field and passions and the research which he conducted.   

This was my first readerly exploration, so I chose to begin with a task that would better prepare me for reading the text.  The author information above was the result of my pre-reading author research.  The formula I used for this exploration was:

Engage in the reading process to increase the likelihood of text comprehension (pre-reading, reading, responding, exploring, applying) + Before you read, learn something about the author(s) of the assigned course reading(s) and note how what you learned impacts your motivation and/or your purpose for reading

As stated above in the formula, I began the process by doing some background research on the authors of the texts, in which I included the most relevant information that would be helpful in adding meaning to my reading.  Since the main idea of these articles centers around learning literacy, I used this as my trigger word in my pre-reading author research.  I included to the best I could any information regarding accomplishments or titles that dealt with literacy teaching and learning.  Doing this research allowed me to tap into the minds of the authors in order to better understand their motivation and passions behind literacy, and to put a face and context to what were only names in my mind.  After reading some background information, I preceded to read the articles and highlighted main ideas and results.  The reading itself was not challenging, as it was very interesting and though provoking, however, I did initially struggle to find the key connection between the articles.  In the search for this essential connection, I skimmed the articles and reviewed my highlighted information to draw conclusions about the two pieces.  I concluded that the one main idea presented surrounds the truth of student engagement in active literacy learning, and the importance of the bigger picture of literacy in the lives of children. Something that I will strive to implement into my future literacy classroom is the promotion of an environment of outward learning – where students take initiative and participate actively with their own thoughts as well as those of their peers.  Overall, these articles and knowledge of the authors enhanced my understanding of both the student and teacher roles in the literacy classroom, as well as demonstrated a successful means of thinking about and doing literacy in the classroom and beyond.  From incorporating this particular readerly task into my reading process, I realized how beneficial it is to have some sort of author background prior to reading a text, and I will continue to adopt this practice into my life as a reader.

This photo was taken to capture a moment of pre-reading author research!

References

About Brian Cambourne. (n.d.). Retrieved from http://www.cambournesconditionsoflearning.com.au/about-brian-cambourne.html

Britsch, S. J., & Meier, D. R. (1999). Building a Literacy Community: The Role of Literacy and Social Practice in Early Childhood Programs. Early Childhood Education Journal, 26(4), 209-215.

Cambourne, B. (1995). Toward an educationally relevant theory of literacy learning: Twenty years of inquiry. Reading Teacher, 49(3), 182.

Daniel Meier. (n.d.). Retrieved from https://edd.sfsu.edu/content/daniel-meier https://edd.sfsu.edu/content/daniel-meier

Susan Britsch //. (n.d.). Retrieved from https://collaborate.education.purdue.edu/edci/britsch/default.aspx

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