Skip to main content

Google Innovators Project - Personalised Learning that makes Real Impact on Student Engagement and Achievement

Section 1 - Context
It should be a reasonable expectation that all children would have equal opportunity for
educational success which will be reflected through equivalent outcomes of assessment
irrespective of class, ethnicity or gender. This paper examines the interplay between
curriculum, instruction, feedback and focuses on assessment and has been the provocation
for the development of my google innovators project where my inquiry question was how can
personalised learning be facilitated to ensure deep engagement and meaningful learning.
The context for this task is a Stage 3 mixed ability, mixed gender classroom of 114 students.
There are 5 teachers collaboratively co-teaching and planning the differentiated program
which is taught through a blended personalised approach. This method includes face to face
whole home class (28 students) explicit teaching (Mini-Lessons), flipped videos, self-paced
learning contracts and matrix's, small group clustering and personalised one on one coaching.
It uses a common language to ensure all students succeed academically by allowing them
access to high-quality instruction (Dean, 2012). The teaching and learning is built using
constructionist methodologies (Vygotsky, 1962; Piaget, 1967; Papert & Solomon, 1971) and
a mixture of SOLO taxonomy (Biggs & Collis, 2014), High Possibility Classroom (Hunter, 2015),
Bloom's taxonomy (Amer, 2006) and TPACK models (Koehler & Mishra, 2009) where teachers
support students by integrating technologies to encourage self-efficacy. The original concept
developed as part of this project has been iterated and enhanced through collaboration with
my team Richelle Hatton, Peter Butchaski, Eli Lindeback, Kat Leech, Matt Burns and Mell
Chuck. It has also been supported by my Google Innovator program mentor Justine Driver, Principal
of Sunnyhill's Primary School in Auckland.
Students are offered self-regulation and independent mastery tasks (Meichenbaum
& Biemiller, 1998) that promote the school's learner profile elements of Knowledgeable and
Resourceful Thinkers, Creative and Critical Inquirers, and Relational and Collaborative
Contributors. Iterations of this project have been applied to other areas of learning and have
had significant impacts with relation to the development of STEM, an inquiry pedagogy and
integration of technology.
The example unit of work for this article has developed was for mathematics in the topic area of Multiplication and Division and the outcomes MA3-1WM, MA3-2WM, MA3-3WM with the focus outcome being MA3-6NA; however, matrix's are now developed for all areas of the curriculum. It spans three to four weeks depending on the student and is completed in class and as the mathematics component of their homework. Prior to students engaging with this unit and pre-assessment they view an introduction teacher made video to ensure all students receive the same information about the topic background, NESA expectations and what they are expected to know, understand and do by the end of the unit of work and demonstrate through the summative assessment (2012a). Often, this introduction will include a real world application to draw links between the curriculum and life outside of school (Hurst, 2011). The aim is to create a hook, generating engagement from the outset so that students can see the purpose of learning about the content. For this Mathematics unit of work students either complete part 1 (Year 5) or part 2 (Year 6) based on their understanding demonstrated in the diagnostic assessment; however, teacher judgment and data drawn from work samples are used to adjust based on need throughout the unit of work allowing for fluid and flexible learning. With each of the matrix's there is a teacher view, student view and support T2S.
(Click on the above image to look at the matrix)

Section 2 - Design
Rationale
Assessments provide meaningful data and information to stakeholders (teachers, parents,
government and the students themselves) about the progress and achievement with relation
to a specific outcome or learning intentions (Dean, 2012). These learning intentions are students
personal stretch targets created through consultation with the teacher (Masters, 2013). The
assessments are snapshots of progress “to establish and understand where the learners are in
an aspect of learning” (Masters, 2014) from the initial formative entry point, to progressive as
learning and summative. A majority of the assessments used include reflective aspects to allow
students increased ownership and agency (Valerio, 2012) of the learning progress based upon
the success criteria. They should inform teaching and improve learning; use multiple sources of
information; and provide valid, reliable, and fair measurements (McTighe & Ferrara, 1998).
While the summative assessment is used primarily to report to parents, the diagnostic and as
learning assessments aid to create a whole picture of the students knowledge, understanding
and ability to apply.
For all intents and purposes these are then shared through the e-portfolio to parents. This is
done to create a constant flow of assessment information between school and home reducing
the possibilities of reporting shock and increasing collaboration with parents (Ntuli &
Kyei-Blankson, 2015). It gives students the evidence of the growth they need to confidently
share with parents and teachers attending their student led conference. Using this framework
assists to celebrate successes when students are pushed into the zone of proximal development
(Vygotsky, 1978 as cited by Masters, 2013) and leverage their strengths to address developing
areas. As this model of learning has been developed there is a deliberate intention to make the
learning significant as students gain the incentive to satisfy their own curiosities and interests
(Sternberg & Williams, 2002) through voice and choice (Miliband, 2006) therefore, creating a
culture of personalised continual improvement whilst the learning is happening (Stiggins, Arter, Chappuis & Chappuis, 2004). This framework additionally allows for adaptability and differentiation
based on student need and in response to the data presented through the multiple snapshot
assessments described below.

Formative Diagnostic Pre-assessment (Student work samples)
The pre-assessment is designed to establish a baseline of what students know so that skills produced
are focused on areas that are developing or are gaps in learning. Within the context of our learning this
data is used to identify the tasks the individual student are required to master along their personalised
learning pathway known as their matrix. Therefore, this assessment serves to connect learning goals to
tangible classroom activities (Wiggins, 2012). The student will receive written feedback based on this
assessment identifying specific skills and tasks they will be required to demonstrate mastery in throughout
the unit of work. This becomes the basis of learning differentiation amongst students as different students
will have highlighted different tasks to complete within their learning matrix.

(Click on the above image to look at the pre-assessment)

Formative As Learning - Mastery (Student work samples and teacher judgement)
The as learning assessments are conducted through a mastery methodology (Meichenbaum
& Biemiller, 1998) which is also known as over learning (Rosenshine, 1983). Within this methodology,
students complete questions related to live teaching or flipped video (Bergmann & Sams, 2014)
displaying the control of the concept at the rate of 85%. As it is a supportive environment, high
expectation of students’ individual learning has created a willingness and culture of iterating understanding
where students fail up (Hinde-McLeod & Reynolds, 2007). This mastery rate gives the student and teacher
tangible and trackable data relating to skill (Wiggins, 2012) placing at the fingers of teachers the information
they need to follow-up the student in smaller one on one coaching session or mini lesson workshop (Tovani,
2012). The feedback students receive is either computer generated, recorded audio, face to face oral or
written depending on the task.

Formative As Learning - Check-in (Interviews and teacher judgment)
As students master the concept in each of the task they check-in with teachers to cross reference task
completion. It is a desirable time for teachers to use questioning to check for understanding (Killen, 2003)
providing evidence regarding student achievement (NESA, 2012a) and promotes deeper understanding as
students confer with teachers. This learning conference provides teacher with rich data that allows them to
strategically provide the student tools for meaningful engagement and actionable application in new situations
(Wiggins, 2012) as they move on to their secondary or extension tasks. Additionally, it provides students a
safety net to ensure that within such a large environment they are not getting lost as they are provided with the
personalised feedback regarding to areas that they can continue to develop showing that they are individually
known and understood as learners.
This check-in furthermore provides the teacher with data that they can use to analyse their own teaching with
relation to the student learning. The feedback the students receive is oral; however, many of the student choose
to take additional notes as they understand that this check-in is also a coaching session. The benefit of this
check-in is that teachers make students reply to feedback by commencing dialogue, allowing the teacher to
identify if the student has embodied the understanding. This feedback is not praise or evaluation; however,
it is a user friendly redirection point with relation to their efforts towards their learning goal (Wiggins, 2012).

Formative As Learning - Observation (Teacher judgement)
The teacher will use their observations as a litmus test of engagement and understanding. They use strategies
such as questioning to check for understanding and ascertain the areas that require additional functioning
developed. Often this will lead to a small cluster of students being pulled together as a focus group mini lesson
or one on one coaching to explicitly zoom in on a particular element of need or enrichment. While these mini
lessons are shared in a small group, they are recorded to allow all students to self assess their need to engage
with these after the teaching.
Therefore, maximising the feedback opportunity by using it as a learning opportunity (Hicks, 2014). This offers
oral, immediate and timely feedback (Wiggins, 2012) based on the discussion of the individual or focus group
(Tovani, 2012); however, within this mini lesson or workshop there is written feedback given on the student work
sample with relation to the success criteria.

Formative As Learning - Bridging Task (New situation student work samples)
The bridging activity provides students as they move from the primary to secondary and the secondary to
extension another point to demonstrate their understanding by creatively producing content designed to
teach the concept in a new situation (Earley & Kanfer, 1985) helping to extend and apply their knowledge
(Dean, 2012). As they make tutorial videos, posters, models and dioramas, raps and animations for a
specific real world audience (Hurst, 2011) and gain peer feedback using the RISE Model (Wray, 2017) of
reflection, inquiring, suggesting then evaluating to ensure their understanding follows the desired methods
or strategy (Hattie & Timperley, 2007). As students are immersed in these rich tasks (Small, 2012), relevant,
purposeful and deep understandings of subject matter are created and connected to real world contexts
(Jorgensen, Walsh & Niesche, 2009). A byproduct of this process, has been observed that there is a higher
commitment level to achieving their personal stretch targets from those who self select to view and evaluate
other peers creations, this is supported by Earley & Kanfer (1985). They gain written or audio teacher and
parental feedback on this through their e-portfolios to clarify and encourage understanding and application.
This is an important element within the feedback loop as it highlights those who have the ability to adjust their
product in light of the feedback received (Wiggins, 2012).

Formative As Learning - Reflections (Student work samples and interview)
As students produce formative and summative material they upload this to their e-portfolios. They are required
to reflect upon their understanding and the process of learning and how they could have enhanced this given
additional opportunities. As they do this, new applications of the concept often come to them based out of their
deeper engagement with the concept (Taras, 2003). This leads to additional feedback conversations with the
teachers as they provide additional scaffolds to create further connections for the student based on the learning
intention (Tovani, 2012).  

Summative Assessment of Learning Post-test (Student work sample)
The post test is used to identify reportable data with reference to the stage outcomes prescribed by NESA (2012b).
This is conducted in two sections, the first section is based upon student learning within the unit and has an element
of strategy recall. The second section is where the student is given a new situation to apply their knowledge and
understanding. The feedback they are provided with is written; however, where students fail to show understanding
in elements that they demonstrated mastery in during the unit of work, teachers will have feedback conversations with them to ascertain why they were unable to show what they know. If teachers judge that it was anxiety, misinterpretation
of the question or additional adjustments were needed due to a learning difficulty they inform the parents and give the
student an additional attempt to demonstrate their understanding of the concept.

(Click on the above image to look at the assessment)

End of unit survey (Feedback for the teacher)
At the end of each of our units we survey the students to identify areas of the unit that were beneficial, academically
engaging and caused challenge for the student (Black & Wiliam, 1998). This data allows us to strategically design
and develop the learning sequence and understand what elements have the greatest impact on student engagement
(Tovani, 2012). Often the teachers will graph this data and present it to their home class which allows them to discuss
the design and highlight which “learning activities are worthy of students’ efforts, are relevant to students’ lives and
require higher order thinking” (Brophy, 2004, as cited by Dean, 2012 p.20). This conversation is used to identify any
gaps in the data (Tovani, 2012) and provides the teacher with addition feedback on the impact of learning (Hattie, 2012).

Section 3 - Justify
Good assessment is about expanding the repertoire to generate a richer, more broad image of the students' performance,
allowing them multiple access points to prove and deepen their understand, knowledge and application (McTighe & Ferrara,
1998). Each of the above mentioned assessments allow teachers to modify and adjust the personalised learning pathway
of the students ensuring that each student has equal opportunity to demonstrate their best performance with relation to the
learning intention and success criteria (Hattie, 2008). This endeavours to ensure learning equity and growth with relation to
the learning outcomes (Gray & Sharp, 2001). Supplying students with as Wiggins, McTighe, Kiernan & Frost (1998) describe,
a track to exhibit their efficacy with relation to the six facets of understanding - explanation, interpretation, application,
perspective, empathy and self-knowledge.
There is compelling research on assessment that determines the significance of feedback to the students learning process
(Taras, 2003; Stiggins, 2004; Nicol & Draper, 2008; Hattie, 2012; Tovani, 2012, Wiggins, 2012). It is contended that formative
assessment is "specifically intended to provide feedback on performance to improve and accelerate learning" (Sadler, 1989
p. 77). Therefore, assessment and feedback teamed together become useful contributions to the learning and teaching
process. It can be drawn from the work of Hattie & Timperley (2007) that when teachers offer the right feedback as an
assessment for learning at the right time can empower efficacy and improve engagement. In Mandinach & Gummer’s (2012)
report they discuss how data can be used to inform educational decision-making and maximise student academic growth. In
this report they highlight differences between the educators data literacy and assessment literacy and how this has impact on
students. They identify that the data literate educator looks at information beyond the student outcome and endeavours to
triangulate information from multiple sources and provide this feedback of emerging patterns to students. Whereas the
assessment literate educator generally focuses on individual assessments and the interpretation of these to inform their
reporting of student performance and decisions about this without triangulation from other data and providing feedback
about visible patterns coming from these assessments. There are multiple examples from within our own Australian context
where the need for data literacy is evident (ACER, 2005; Renshaw, Baroutsis, van Kraayenoord, Goos, & Dole, 2013). Much
of the drive comes from the desire to utilise evidence based approaches to student learning; however, Goss & Hunter, (2015)
indicated teachers require growth in the utilising the various kinds of data that exist to ensure accuracy, improvement for the
student and informed decision making.
Providing personalised learning based upon personalised assessments engages and respects students as individuals by
tapping into their passions and interests. As a result, students enjoy accessing the curriculum as they have choice, breadth
of study, challenge and personal relevance. They also know the pathway and the success criteria that the use to track their
growth as they move towards attaining their learning goals (Miliband, 2006). From personal experience the evidence shows
that measurable growth can be tracked using this system of personalised learning.

Section 4 - Links
As facilitators of learning, the desire is to create a learning environment where students question, discuss, inquire and
collectively solve problems that affect their world. As a consequence our education system requires teachers to equip
children with strategies for rigorous intellectual activity (Wiggins, 1993) using assessments that commends each child's
progress and provide them with the feedback to enhance their understanding and ability to apply this in more advanced ways.
In the unit given each of the tasks are aligned to the content descriptors that feed into the overall Mathematics outcome.
Therefore, feedback and teaching become quite specific micro-learning episodes based on ongoing assessment (Semingson,
Crosslin & Dellinger, 2015).
Therefore, both formal and informal authentic student assessment must reinforces the content mastered throughout the unit,
helping students communicate their understanding and develop deeper insights. While for the teacher it guides the
interventions they will make within learning (Mosier, 1951). Rich assessment supports students retaining and transferring
the material and understanding to their long term memory as students have multiple stimuli that engage with the prior
knowledge stored in loops of brain cell connections (Willis, 2006). Activating these strong memory circuits is enhanced
by assessments that are frequent, spaced throughout (Tinto, 2012), built on the student and teacher interplay that allows
students to perform and be tracked on multiple levels (Taylor & Rohrer, 2010), focuses on over learning to the point of
mastery (Rosenshine, 1983) across situations and ideally low stake (Brown, Roediger & McDaniel, 2014). Adding to this
approach uses meaningful feedback to provided to students about what they need to do next in order to advance their
learning is crucial.
Stiggins (2005) stated that “to use assessment productively to help achieve maximum student success, requires certain
conditions need to be satisfied” (p. 4). The author believes the use of the assessment forms discussed helps maximise
the student long-term success as they generate the evidence of students curriculum understanding based on formal
assessment, teacher observations, peer feedback, self-assessment, work samples and computer generated tasks.
This evidence of student learning assists teachers to determine achievement against outcomes and standards and
provides them with the opportunity to plan future learning goals and pathways for students (NESA, 2012a).

References:
Amer, A. (2006). Reflections on Bloom's revised taxonomy. Electronic Journal of Research in Educational
Psychology, 4(8).
ACER (2005). Using Data to Support Learning (Conference Proceedings), Australian Council for Educational
Research (ACER).
Bergmann, J., & Sams, A. (2014). Flipping for mastery. Educational Leadership, 71(4), 24-29.
Biggs, J. B., & Collis, K. F. (2014). Evaluating the quality of learning: The SOLO taxonomy (Structure of the
Observed Learning Outcome). Academic Press.
Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: principles,
policy & practice, 5(1), 7-74.
Brown, P. C., Roediger, H. L., & McDaniel, M. A. (2014). Make it stick. Harvard University Press.
Dean, C. B. (2012). Classroom instruction that works: Research-based strategies for increasing student
achievement. ASCD.
Earley, P. C., & Kanfer, R. (1985). The influence of component participation and role models on goal
acceptance, goal satisfaction, and performance. Organizational Behavior and Human Decision Processes,
36(3), 378-390.
Jorgensen, R., Walsh, L., & Niesche, R. (2009). Reforming schools: A case study of New Basics in a primary
school. International Journal of Leadership in Education, 12(2), 115-133.
Hattie, J. (2008). Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Routledge.
Hattie, J. (2012). Visible learning for teachers: Maximizing impact on learning. Routledge.
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of educational research, 77(1), 81-112.
Hicks, T. (2014) Make It Count: Providing Feedback as Formative Assessment, Edutopia retrieved from
https://www.edutopia.org/blog/providing-feedback-as-formative-assessment-troy-hicks
Hinde McLeod, J., & Reynolds, R. (2007). Quality teaching for quality learning: Planning through reflection.
Katoomba, NSW: Thomson Social Science Press.
Hunter, J. (2015). Technology integration and high possibility classrooms: Building from TPACK. Routledge.
Hurst, C. (2011). Engagement and connection in mathematical learning. Prime Number, 26(3), 3.
Goss, P., & Hunter, J. (2015). Targeted teaching: How better use of data can improve.
Gray, D., & Sharp, B. (2001). Mode of Assessment and its Effect on Children's Performance in Science.
Evaluation & Research in Education, 15(2), 55-68.
Killen, R. (2003). Effective Teaching Strategies: Lessons from research and practice
(3rd edn). Katoomba, NSW: Thomson Social Science Press.
Koehler, M., & Mishra, P. (2009). What is technological pedagogical content knowledge (TPACK)?.
Contemporary issues in technology and teacher education, 9(1), 60-70.
Masters, G. N. (2013). Towards a growth mindset in assessment. Practically Primary, 19(2), 4.
Masters, G. N. (2014). Assessment: getting to the essence. Center for Assessment Reform and Innovation,
ACER.
Meichenbaum, D., & Biemiller, A. (1998). Nurturing independent learners: Helping students take charge of
their learning. Brookline Books, Cambridge, MA.
McTighe, J., & Ferrara, S. (1998). Assessing Learning in the Classroom. Student Assessment Series. NEA
Professional Library, Annapolis Junction, MD.
Miliband, D. (2006). Choice and voice in personalised learning. Centre for Educational Research and
Innovation (Ed.), Schooling for tomorrow personalising education, 21-30.
Mosier, R. (1951). The Educational Philosophy of Reconstructionism, Journal of Educational Sociology,
American Sociological Association.
NESA (2012a) Advice on Assessment retrieved from
https://syllabus.nesa.nsw.edu.au/support-materials/advice-on-assessment/
NESA (2012b) Mathematics K-10 Syllabus retrieved from
https://syllabus.nesa.nsw.edu.au/mathematics/mathematics-k10/
Nicol, D., & Draper, S. (2008, July). Redesigning written feedback to students when class sizes are large.
In Improving University Teachers Conference, July, Glasgow.
Ntuli, E., & Kyei-Blankson, L. (2015). Planning, designing, and implementing effective interactive portfolios
in the primary grades: Suggestions for forming partnerships among teachers, students, and parents. In
Young Children and Families in the Information Age (pp. 133-147). Springer Netherlands.
Papert, S. & Solomon, C. (1971). Twenty things to do with a computer. Artificial Intelligence Memo No.
248 and Logo Memo No. 3.
Piaget, J. (1967). Biologie et connaissance [Biology and knowledge], Gallimard, Paris. Google Scholar.
Renshaw, P., Baroutsis, A., van Kraayenord, C., Goos, M., & Dole, S. (2013). Teachers using classroom
data well: Identifying key features of effective practice.
Rosenshine, B. (1983). Teaching functions in instructional programs. The elementary school Journal, 83(4), 335-351.
Semingson, P., Crosslin, M., & Dellinger, J. (2015, March). Microlearning as a tool to engage students in
online and blended learning. In Society for Information Technology & Teacher Education International
Conference (pp. 474-479). Association for the Advancement of Computing in Education (AACE).
Small, M. (2012). Good questions: Great ways to differentiate mathematics instruction. Teachers College
Press.
Stiggins, R. (2005). From formative assessment to assessment for learning: A path to success in
standards-based schools. Phi Delta Kappan, 87(4), 324-328.
Stiggins, R. J., Arter, J. A., Chappuis, J., & Chappuis, S. (2004). Classroom assessment for student
learning: doing it right--using it well. Assessment Training Institute.
Sternberg,  R.J. & Williams,  W.M. (2002). Educational  Psychology. Boston, MA: Allyn & Bacon.
Taras, M. (2003). To feedback or not to feedback in student self-assessment. Assessment &
Evaluation in Higher Education, 28(5), 549-565.
Taylor, K., & Rohrer, D. (2010). The effects of interleaved practice. Applied Cognitive Psychology,
4(6), 837-848.
Tinto, V. (2012). Completing college: Rethinking institutional action. University of Chicago Press.
Tovani, C. (2012). Feedback Is a Two-Way Street. Educational leadership, 70(1), 48-51.
Valerio, K. (2012). Intrinsic motivation in the classroom. Journal of Student Engagement: Education
Matters, 2(1), 30-35.
Vygotsky, L. S. (1962). Thought and Language. 1934. Trans. Eugenia Hanfmann and Gertrude Vakar.
Cambridge, MA: MIT P.
Wiggins, G. P., McTighe, J., Kiernan, L. J., & Frost, F. (1998). Understanding by Design. Association
for Supervision and Curriculum Development, Alexandria, VA.
Wiggins, G. P. (2012). Seven Keys to Effective Feedback. Feedback for Learning 70(1), 10-16.
Willis, J. (2006). Research-based strategies to ignite student learning. Alexandria, VA: Association
for Supervision and Curriculum Development.
Wray, E. (2017). RISE Model for Peer Feedback retrieved from http://www.emilywray.com/rise-model

Comments

Popular posts from this blog

How do we Build a Culture of Inquiry and Data Use?

School systems have a shared responsibility to improve student learning outcomes. Likewise, for staff there is an obligation to provide extended opportunities to build on what they already know. High quality recording methods that ascertain growth mapped over time can identify trends and highlight threats allowing organisations to predict implications of applying a learning initiative or intervention. This can become complex and messy due to competing agendas and a variety of interpretations. For this reason, organisations have an obligation to develop a fair, ethical and shared understanding how data will be used and interpreted (Stoll & Fink,1996). A strong and user-friendly data system when properly implemented, empowers teachers to discover value in functions that bring student data to their fingertips (Brunner, Fasca, Heinze, Honey, Light, Mandinach & Wexler , 2005). Therefore, teachers require adequate learning support if they are to use data to improve practice

Managing the use of Artificial Intelligence (AI) in the classroom

As educators, we all understand the importance of ensuring that students submit their own work and are not cheated of their success by others. However, with the increasing use of artificial intelligence (AI) in the classroom, it can be difficult to ensure that students are not cheating on assignments. Fortunately, there are a number of measures that educators can take to minimise the possibility of cheating while still using AI to their advantage. Here are a few tips to help you manage the use of AI and minimise cheating by students on assignments. 1. Set Clear Guidelines The first step in preventing cheating is to set clear guidelines about the use of AI and make sure that students understand the expectations. Make sure students are aware that AI-generated work is not permitted and that any work submitted must be their own. 2. Monitor Student Activity Monitoring student activity through AI can help you identify any potential cheating. AI can be used to detect plagiarism and other sign

What does a post-industrial class look like? Part 2

This post is the second part of a series that I have been working on to identify what  does a post-industrial class look like? In my previous post , I looked at using video, collaborative discussion, grouping and student-centred learning. Why a large display and one to one? The large electronic display is used as it offers many benefits to a given lesson; these include demonstration and modelling as the teacher could showcase the application or video from the board (Moss, et al, 2007). It is easy to show the important features of particular web-based activities and have students interact with the material on their own devices. The board can accommodate different learning styles (Herrington & Harrington, 2006). Interactive boards can help tactile learners by touching and marking the board. Audio learners can have the class discussion and auditory multimedia, visual learners can see what is taking place as it develops at the board and it offers multimodal learning which can b