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Showing posts with label #EdChat. Show all posts
Showing posts with label #EdChat. Show all posts

The Need for Disruptive Education

#EdChat, Education and Learning, Executives' School 0 comments

Centro de la Cultura Herediana, Heredia, Costa Rica
Picture taken by Jonathan Acuña (2017)

The Need for Disruptive Education

Some considerations


         Do students want or have to listen to their teachers? Long ere this thought of a disruptive education, in which educators only wanted their students to sit down and listen to them, but the fact is that there are several education paradigms like the one above that prevail and that only make us think of how things have always been done in only one way. And there we have instructors on top of paradigm watchtowers preventing colleagues from making changes in the education their pupils are getting today. Learners should want to listen to their teachers because they can help them construct their knowledge and will not make them regurgitate what was mentioned in class.

         If tickets to attend one’s class were sold, will one’s students buy them? With this question Lewin (2020) makes educators question their role in the classroom and the teacher’s soliloquy employed at times in class where no higher order thinking skills are employed by learners. Lewin longs to have sight of disruptive classrooms where paradigms are constantly broken for the sake of student learning. Education is not just about regurgitating information; it has to go through various channels to become learning. As pointed out by Peter, de Roche, Graf, & Gatziu Grivas, (2019), “skills are used to designate the ability to use one’s knowledge with relative ease to perform relatively simple tasks.” And when these skills are pracited in class they can become competencies. And when students can develop competencies in class one’s class tickets will always be sold out. Learning will always be present to engage pupils at all times.

For a while, the traditional educators will remain in thought, and they will continue to be the warders of education with recurrent paradigms or will embrace a disruptive education willfully. It is not right to sulk about the need for refocusing learning; what educators have to do is to start selling tickets for their classes because, as Lewin (2020) insists, this disruption will generate critical thinking, creativity, and a desire for learning, which will make students’ skills become competencies. In other words, the competence of a learner or cohort of pupils must “describe the relationship between the tasks assigned to or assumed by the person or group and their capability and potential to deliver the desired performance” (Peter, de Roche, Graf, & Gatziu Grivas, 2019). When a desired performance is achieved, students will be learning by doing and coming to class for the pleasure of constructing their knowledge and participating in experiences that will strengthen their competence.

A disruptive education, free of aged, decrepit, enfeebled paradigms, will feed a growth mindset with room for risk-taking experiences and failure. Lewin (2020) states that capitalized mistakes is pure learning, which is pretty much what Oscar Wilde (2005) once said about experience: “it is merely the name men give their mistakes,” and students need to make mistakes to consolidate their learning. Engaging students in their learning is by far the best lesson of life you can give them; “I can do it” (Lewin, 2020). And they will be able to make mistakes and learn and will learn to become autonomous, self-disciplined, and self-regulated.

References

Lewin, L. (2020, Setiembre 15). La Innovación LLega al Aula. Escuela para Directivos, Laureate Languages. Buenos Aires, Argentina: ABS International.

Peter, M., de Roche, M., Graf, M., & Gatziu Grivas, S. (2019, June). Skills and Competencies for Digital Transformation. Retrieved September 21, 2020, from ResearchGate.Com: https://www.researchgate.net/publication/336375389_Skills_and_Competencies_for_Digital_Transformation_Initiatives_-_Development_of_a_model_to_identify_relevant_skills_and_competencies_for_a_company's_individual_digital_transformation_roadmap

Wilde, O. (2005). The Picture of Dorian Gray. Clayton, Delaware: Prestwick House Literary Touchstone Press.

 


The Need for Disruptive Education by Jonathan Acuña on Scribd


Tuesday, September 22, 2020



Active Learning Through the Flipped Classroom

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“Un École,” The Medina of Tunis, Tunicia
Picture taken by Jonathan Acuña (2019)

Active Learning Through the Flipped Classroom

Making great use of class time

 


         When teachers think of what the best way to invest class time is, they must think of active learning. And “active learning refers to a broad range of teaching strategies which engage students as active participants in their learning during class time with the instructor” (Univerity of Minnesota, 2020). Nowadays education does not have to leave an aftertaste of the school as a knowledge factory. Based on Lewin (2020), schools do not usually promote critical thinking since the classroom must be a place to understand a topic, and then do something with the newly-acquired information. Active learning has to be present; the idea is to involve learners in individual work, reflection outside the classroom, and engaging tasks in class.

         How can active learning be attained? Students in the traditional classroom are beseeching their teachers mutely not to desert them on their education; the flipped classroom can be the way, according to Lewin (2020), to maximize, capitalize, and potentiate F2F interactions with learners with practical tasks in the schoolrooms. And this change in teaching paradigms is necessary because “flipped learning is a pedagogical model where traditional instructional goals for what happens inside and outside of class are reversed and student learning becomes increasingly active” (Wagoner, Nechodomu, Falldin, & Hoover, 2013). In other words, learning spaces require to empower students to make decisions in terms of their own learning that begins outside the classroom. By all the written and unwritten maxims of active learning, pupils have to be offered with solutions for the maximization, capitalization, and potentiation of their education.

Taken from Wagoner, Nechodomu, Falldin, & Hoover (2013)

         Do teachers want pupils to be at their lowest ebb when it comes to learning and active participation in the classroom? In the miasma of traditional classroom teaching, the active learning instructor is ready to break the paradigms. And the breakthrough begins with putting Bloom’s taxonomy upsidedown (see picture above). With a radical change like this, as Lewin (2020) states, education must develop higher order thinking not lower order thinking. Lewin (2020) also insists on the importance of becoming a facilitator not just a teacher; in this way the instructor helps learners to comprehend new concepts, guides students to find their own answers, and observes student development and the building of their own knowledge that gets to be applied in other contexts when necessary.

         What needs to start happening? Active learning facilitators want to get their learners out of the spot where they are being gagged and blindfolded by traditional education. By setting students free, they can work on the first two layers of Bloom’s taxonomy out of class; facilitators can then work with the other three layers (application, analysis, and synthesis) and the capstone (evaluation) in class. Now it is the time to, as Lewin (2020) says, to hold interesting experiences. These tasks will empower students to maximize, capitalize, and potentiate their learning aided by their teachers because this “allows more time for instructors to interact with students, and students to interact with each other” (Wagoner, Nechodomu, Falldin, & Hoover, 2013) efficiently profiting from their time in the classroom learning by doing.

Perhaps it is tell-tale as some educators uninterested in student learning have stated before, but education can be fun for pupils as well for instructors when it comes to flipping and active learning. As described by Lewin (2020), we have to attain flipped learning a) to promote participation, b) to boost social skills and student interaction, c) to fix learning in the middle of class action, d) to favor independent and interdependent learning, e) to facilitate learning at one’s pace, f) to use time effectively, g) to let students think in and out of class, and h) to let absent learners advance at home. For very traditional educators, there will be no elation in their gait to teaching, but “in an active learning approach, students learn by doing” (Wagoner, Nechodomu, Falldin, & Hoover, 2013), and as asserted by Lewin (2020), students will learn to swim by swimming; there is no other way.

References

Lewin, L. (2020, Setiembre 1). El Aula Invertida. Escuela para Directivos. Buenos Aires, Argentina: ABS International.

Univerity of Minnesota. (2020, September 2). Active Learning. Retrieved September 7, 2020, from Center for Educational Innovation: https://cei.umn.edu/active-learning#:~:text=Active%20learning%20refers%20to%20a,individual%20work%20and%2For%20reflection.

Wagoner, T., Nechodomu, T., Falldin, M., & Hoover, S. (2013). CEHD Flipped Learning Guide. Minneapolis-Saint Paul, Minnesota, USA: College of Education. Retrieved Setiembre 7, 2020, from https://academics.cehd.umn.edu/digital-education/wp-content/uploads/2017/05/CEHD-DEI-Flipped-Learning-Guide.pdf

 


Active Learning Through the Flipped Classroom by Jonathan Acuña on Scribd


Monday, September 07, 2020



The Classroom as the Learning Protagonist

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“Virgil and the Muses,” Musée du Bardo, Tunis, Tunisia
Picture taken by Jonathan Acuña (2019)

 

The Classroom as the Learning Protagonist

Who are classrooms for?

After listening to Laura Lewin (2020), on the Laureate Languages Webinar “Arquitectura Escolar: El Aula como Protagonista,”her stream of thought made me wonder a lot about how the classroom space needs to be rethought. Though Lewin (2020) focused her presentation on brick-and-motar classrooms, this type of education has not changed much in the last 100 to 150 years. At that time, as explained by Lewin (2020), the only one source of knowledge and information in this distant past was the teacher. The fact is that today input to build one’s knowledge comes from a great gamut of sources. But when I continue to think of Lewin’s teachings, it makes me continue to wonder about the virtual classroom more and more and how similar both teaching/learning environments are.

Regardless of the type of classroom one is teaching in, think for a moment what the objective of the classroom is. Who benefits from the virtual classroom, the student or the teacher? “Among the many advantages of an online education, you’ll find virtual classroom are great for people who are advancing their education while working” (Drexel University School of Education, n.d.). Based on this statement, and following what Lewin (2020) explains, it is the learners who need to stake their claims in this virtual environment; the teacher becomes a mediator of knowledge and information that can come from a great amount of sources, from books to Webpages. For Lewin (2020), the classroom must awake student curiosity and collaboration. And there is no reason why a virtual classroom cannot huddle close to a curious mind and a collaborative individual willing to further his/her education.

When it comes to think about the place where a virtual classroom is held by the students and their teacher, what kind of message is being conveyed by the physical spaces these people use for a lesson? “A virtual classroom is a digital teaching and learning environment in which participants can interact with learning resources and with one another like they can in a traditional classroom” (Chin, 2017), but think for a moment: “Places do convey a silent but powerful message” (Lewin, 2020) for both teachers and students. A crappy, junky place where a teacher or student has a class is saying a lot about any of these two individuals. A camara off, e.g., on the side of the student is, says Lewin (2020), like if the learner is taking the class below his/her desk or working table. All class participants must be in places that look neat; Lewin (2020) also suggests that it has to be a noise-free, comfortable environment that will not generate stress on students and teachers. Isn’t all this applicable to vitual or F2F teaching and learning?

Bates (2015) stresses the idea of experiential learning in education because it “focuses on learners reflecting on their experience of doing something, so as to gain conceptual insight as well as practical expertise.” For Lewin (2020), we all learn more by doing than by watching and listening. Learning is an active process, and one’s ability to retain and then retrieve information that can be later on used in a different context is what needs to be developed in the classroom. When students are challenged, as part of the novelties in a classroom, as Lewin (2020) says, it invites to foster learning. The classroom environment, whether it is virutal or F2F, becomes more and more dynamic and enticing to generate the building of new knowledge.

To sum up, the seeds of good teaching and learning are not just found in a traditional street-side school where learners and teachers interacted F2F. Educating people in virtual environments also bring good learning and the building of new knowledge. Any of the two learning environments are an assemblage of well-calculated practices, people’s behavior, and the good use of a F2F activities leading to collaboration and higher order thinking skills. Let’s hope to guide our students to an active learning process; in an active classroom we must find learners working on different tasks at the same time plus an engaged and creative teacher supervising what is going on in the classroom (Lewin, 2020).

References

Bates, A. (2015). Experiential Learning: Learning by Doing. Retrieved August 31, 2020, from OpenTextBC.Ca: https://opentextbc.ca/teachinginadigitalage/chapter/4-4-models-for-teaching-by-doing/

Chin, Y. (2017, May 27). Delivering Training with Virtual Classrooms. Retrieved August 31, 2020, from UncannyOwl.Com: https://www.uncannyowl.com/delivering-training-virtual-classrooms/

Drexel University School of Education. (n.d.). The Benefits of Online Education in a Virtual Classroom. Retrieved August 31, 2020, from Drexel University School of Education: https://drexel.edu/soe/resources/student-teaching/advice/benefits-of-online-and-virtual-learning/#:~:text=But%20online%20students%20have%20better,for%20both%20learning%20and%20networking.

Lewin, L. (2020, August 25). Arquitectura Escolar: El Aula como Protogonista. Escuela para Directivos. Buenos Aires, Argentina: ABS International. Retrieved August 25, 2020



The Classroom as a Learning Protagonist by Jonathan Acuña on Scribd


Monday, August 31, 2020



Business Understanding, The first stage of Data Science

#EdChat, Big Data, Data Science, The Data Scientist 0 comments

Ruinas de Ujarrás, Ujarrás, Cartago, Costa Rica
Photo by Jonathan Acuña (2018)

Business Understanding
The first stage of Data Science

By Prof. Jonathan Acuña-Solano, M. Ed.

Head of Curriculum Development
Academic Department
Centro Cultural Costarricense-Norteamericano
Senior Language Professor
School of English
Faculty of Social Sciences
Universidad Latina de Costa Rica

Sunday, August 18, 2019
Post 338 / DS Log 7

          Data Science is quite peculiar when it comes to the steps one has to follow in order to start the process of comprehending what exactly needs to be addressed when a company’s problem needs to be explored, understood, and then resolved. But why is it so essential to establish the “business understanding” at the start of the Data Science methodology? Let’s explore some potential answers to this question especially when linked to a very specific problem.


          “Business understanding is the first stage of the data science methodology; it provides clarity about the problem to be solved and the data that should be used” (Laureate Education Inc., 2018). When a data scientist is given a problem that needs to be explained and then solved, that query posed by company stakeholders can be misunderstood if this process is not carried out; it is a matter of perception in the end. The company need to explain the problem they have in full to the scientist(s); details cannot be omitted. The scientist(s) must comprehend the problem to help the company formulate the right questions to obtain the right guidance to gather data. With these discussions among the company and the scientist(s), business understanding will help determine that kind of methodological approach needed: descriptive or predictive.

Business Problem Sample:
1) The scientist has to sit with the school’s academic stakeholders to be explained what exactly the problem is and its current implications for the institution, its reputation, and how graduate students are perceived in the work market in the country.
A language school whose students are not obtaining the expected CEFR outcome at the end of its program
2) Understanding how the school is being affected by a poor performance of their graduating students will help stakehoders to formulate the right question(s) to ask to set the data requirements to gather information.
3) This open and sincere discussion with the school academic stakeholders will provide room to comprehend why the problem needs to be given a solution, the reasons why the current state of affairs has to be amended.


   “To establish business understanding, structured discussions with different stakeholders must happen so that the research focus (goals and objectives) can be classified” (Laureate Education Inc., 2018). It is crucial to clarify at this point that these “discussions” cannot just be held to ask company contributors what they want in terms of the enterprise’s problem; consultations have to be organized to get to the gist of the research focus needed to find solutions to the problem. Team members must come from different areas in a company; business understanding cannot just be provided by one single individual. And through all these deliberations goals and objectives also need to be clearly stated in the minds of company’s stakeholders and the data scientist(s). Forgetting this simple step in business understanding may trigger the wrong results.

Business Problem Sample:
1) Rounds of discussions must be organized with the school academic stakeholders to fully clarify what the gist of the project and its scope are. The research focus needs to be clearly stated because results can be wrong.
A language school whose students are not obtaining the expected CEFR outcome at the end of its program
2) The group of academic contributors must come from different areas of the department. This is not just about an academic director’s perception; it has to come from all areas that constituted the department.
3) All members of the academic team must have clearly stated -in their mind- the goals and objectives of finding the reasons why students are not achieving the correct CEFR level. Everyone has to embrace the project.




     “Once a business understanding is in place, key business partners can remain engaged and provide support and guidance to project members” (Laureate Education Inc., 2018). Company’s team members must remain part of the project; they cannot detach themselves from the data scientist(s) assigned to the business strategy to find solutions to a problem. As active members in the process, company’s partners are present to support the data analysts by providing them with any other vital information (such as databases) to walk the right track towards the finding of (an) answer(s) to the stakeholders’ question(s). The engagement we are talking about is manifested in the establishment of a business understanding and in the guidance needed when scientists may be missing a piece of the puzzle to comprehend the company’s problem.

Business Problem Sample:
1) Though there are structured conversations among the academic stakeholders, they need to remain part of the project and not just stay aside and wait for results. These people help in discovering solutions.
A language school whose students are not obtaining the expected CEFR outcome at the end of its program
2) Academic collaborators support the data scientist(s) when they contribute with information to consolidate the business understanding here linked to the poor CEFR performance of the school’s language learners.
3) Academic engagement will be present all across the process since as team players, they can provide the data science group with guidance especially when a piece of the puzzle is missing in its right position.


     As a first stage in Data Science, business understanding is decisive and imperative. Lack of understanding among all participants in a data science team can lead to formulating wrong questions and obtaining inaccurate answers. In the example used in this presentation of facts associated to the language school, there are plenty of people involved in the search for an answer as to why their learners are not achieving the mastery of the CEFR level the program aims at. Their participation in the process to find answers to the questions they pose as central will determine the goals, objectives, and scope of the possible answers they can obtain. As stakeholders they can make better decisions in regards to what needs to me done to help their students become competent English speakers.




References



Laureate Education Inc. (2018). Asking Questions with Data Science. Retrieved from One Faculty: https://dtl.laureate.net/webapps/blackboard/content/listContent.jsp?course_id=_165016_1&content_id=_801203_1&mode=reset


Post 338 - Business Understanding by Jonathan Acuña on Scribd






Sunday, August 18, 2019



Gray Matter in Data Science: Some Insights in Methodology

#EdChat, Big Data, Data Science, The Data Scientist 1comments

Capilla del Rosario, Santo Domingo Church, Quito, Ecuador
Photo by Jonathan Acuña (2018)

Gray Matter in Data Science
Some Insights in Methodology

By Prof. Jonathan Acuña-Solano, M. Ed.
School of English
Faculty of Social Sciences
Universidad Latina de Costa Rica
Saturday, August 3, 2019
Post 335 / DS Log 6

          When one talks about information found in Big Data, info can be referred as gray matter. Why gray? The answer is simply; it turns gray because in the process of making use of Data Science, when a question is asked, the response cannot be referred as black or white. In other words, the grayness is the result of having various ways of answering a question (problem) stated by stakeholders. Based on Dr. Mustaza Haider (Laureate Education Inc., 2018), a data scientist will not find answers clearly. Responses won’t be found quickly and easily; they are the gray matter that needs to be molded into the answers that institutions need to describe what is currently happening or what could come in the future.

          Based on Laureate Education Inc. (2018), Data Science Metholodology has to follow certain sequential steps to “yield” answers to questions made by stakeholders in an institution. This methodology is here to turn gray matter into a visible black-and-white “object” that can be manipulated, analyzed, and understood. Take a look at the methodological model.

1
Business Understanding
The process begins with the search for clarification about the research focus.
2
Analytic Approach
Next step is to find clarification from the stakeholders who are asking the question.
3
Data Requirements
After that, the data scientist prepares the parameters to meet the desired outcome.
4
Data Collection
The following phase consists of the actual collection of data to answer the question.
5
Data Understanding
Next stage refers to using the collected data to construct the data set for cleansing.
6
Data Preparation
The subsequent maneuver is the actual cleansing of the data from “dirty data.”
7
Modeling
Next procedure implies the development of a descriptive or predictive model for the data.
8
Evaluation
Next in line is to evaluate the depurated data to see if it provides insight into the question.
9
Deployment
Our before-last step is to “move strategically” the collected data to “push out” an answer.
10
Feedback
Finally, refinement of the model created is ready to run or to get adjusted.
Created by Prof. Jonathan Acuña with information from Laureate Education Inc. (2018)
         
          Parallel to these methodological considerations, the following infographic presents what happens when these processes (or methodological steps) are transformed into questions that need to be fully answered to get to provide an answer to what is being asked by institutional stakeholders.


          To conclude, the Data Science Methodology used to answer a question is precise and must be followed to the very detail. Doing otherwise will probably trigger answers that do not provide any light to problem a company wants to explain or an issue that can materialize in the short or long run.


References



Laureate Education Inc. (2018). Asking Questions with Data Science. Retrieved from One Faculty: https://dtl.laureate.net/webapps/blackboard/content/listContent.jsp?course_id=_165016_1&content_id=_801203_1&mode=reset
Laureate Education Inc. (2018). Things Data Science People Say. [Video File]. Retrieved from https://dtl.laureate.net/webapps/blackboard/content/listContent.jsp?course_id=_165016_1&content_id=_801203_1&mode=reset



Gray Areas in DS by Jonathan Acuña on Scribd


Saturday, August 03, 2019



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