# data[].attributes.body
Anderson, L.W., Krathwohl, D.R., Airasian, P.W., Cruikshank, K.A., Mayer, R.E., Pintrich, P.R., Raths, J., Wittrock, M.C. (2001). A Taxonomy for Learning, Teaching, and Assessing: A revision of Bloom's Taxonomy of Educational Objectives. New York: Pearson, Allyn& Bacon.

Bloom, B.S. (Ed.).Engelhart, M.D., Furst, E.J., Hill, W.H., Krathwohl, D.R. (1956). Taxonomy of Educational Objectives, Handbook I: The Cognitive Domain. New York: David McKay Co Inc.
Biggs, J. and Tang, C. (2011). Teaching for Quality Learning at University. Maidenhead, UK: SRHE & Open University Press.

Coffield, F., Moseley, D., Hall, E. and Ecclestone, K., 2004. Learning styles and pedagogy in post-16 learning: A systematic and critical review.

Cognitive load theory: Research that teachers really need to understand. (2017). [online] Centre for Education Statistics and Evaluation, pp.1- 4. Available at: http:///cognitive_load_theory_report_AA1.pdf [Accessed 31 Dec. 2017].

Illeris, K. (Ed.) (2009) Contemporary Theories of Learning: Learning Theorists…in their own words. Routledge.

Learning Theories. (2017). Social Learning Theory Bandura Social Learning Theory. [online] Available at: https://www.learning-theories.com/social-learning-theory-bandura.html [Accessed 1 Dec. 2017].

# data[].attributes.headline
5.Learning Taxonomy Underpinning the theory

# data[].attributes.subject
5.Learning Taxonomy Underpinning the theory

# data[].attributes.body
Bloom's Taxonomy and Webb's depth of knowledge therefore serve important functions in education reform at the state level in terms of standards development and assessment alignment. Because cognitive rigor encompasses the complexity of content, the cognitive engagement with that content, and the scope of the planned learning activities, the CR matrix can enhance instructional and assessment practices at the classroom level as well. Superposing the two cognitive complexity measures produces a means of analyzing the emphasis placed on each intersection of the matrix (Heiss et al 2009)

# data[].attributes.headline
4. Action Undertaken based on the Critical Evaluation

# data[].attributes.subject
4. Action Undertaken based on the Critical Evaluation

# data[].attributes.body
Reviewing the theories and learning styles certain practices were implemented in the lecture based cognitive apprenticeship approach. They are

Modeling

Demonstrate explicit steps and work through a problem aloud, demonstrating her heuristics and procedural knowledge.

Coaching

During Coaching, gives feedback and hints to the novice.

Scaffolding

If the students are unable to do the specified task extra reinforcing sessions are provided with aspects of the task that the student cannot do yet. Several tutorials are provided to practice and impart speed
Articulation
A series of questions are asked to the students to  refine and reinstate their knowledge to arrive in conclusion of the activity
Reflection
The final answers are discussed with the students to compare their answers. The goal of reflection is for students to look back and analyze their performances with a desire for understanding and improvement
Exploration

The students are paired to solve the series of problems and closely monitored for guiding them to reach the solution. After a given amount of time, the students present their solutions to the class, explaining their methods as well as their answers. If another pair of students disagrees, they can present their own solution, and the class decides as a group which answer is correct and which method of obtaining it is easiest, most appropriate. Students thus have the opportunity to construct their own strategies for solving problems and their own understanding of the mathematical concepts involved, and they are more likely to retain those concepts longer than if they had been given them by rote. They also learn valuable oral presentation skills.

# data[].attributes.body
Based on the challenges observed, the learning theories that can be is self- efficacy and surface learning approach. As stated by Bandura, (1997), the individual believes that are able/unable to perform task which is correlated to their past performance. The surface learning causes fear of failure, routine memorizing and intuition to bound minimally on course requirements. This has to be transferred to deep strategic learning that can relate ideas and create interest using evidences that create meaning to their knowledge  (Center for research in to instruction and learning,1997)

There students have to unlearn the traditional learning methods such as the tutor explains the theory and based on it several practice problems are worked and some tutorials are awarded to practice. Simply telling the students these are the knowledge that’s required for the future will not create a motivation. Instead a preferable inductive learning and teaching can be considered. For example a case study or complex real time problem can be solved based on theory taught

·         Initially the instructions should be based on the student’s knowledge likely experience based on the cognitive approach.

·         Materials should be provided on an easily understandable format.

·         Provide instructions to fill the gaps and extrapolate the materials provided this can improve self-learning of students

·         Group work should be encouraged this attributes to social constructivism (Prince,2006)

The motivation of the students can be also improved by tutor’s self disclosure. Sorensen (1989) reported perceived teacher self-disclosure is positively associated with student perceptions of affective learning (e.g., liking of class and teacher). Downs, Javidi, and Nussbaum (1988) found teachers who used narratives and humor, along with self-disclosure, improved the clarity of the information presented for students

Therefore a "metacognitive" approach to instruction can help students learn to take control of their own learning by defining learning goals and monitoring their progress in achieving them (wordpress.com,2012). According to Collins and Newman 1987, a cognitive apprenticeship approach can be adopted. These methods enable students to cognitive and metacognitive strategies for “using, managing, and discovering knowledge. The teaching methods are modeling, coaching, scaffolding, articulation, reflection and exploration.

# data[].attributes.body
A prior knowledge of basics of Mathematics like algebra only required to apply and integrate knowledge and understanding of engineering disciplines to support the study . The class is of different nationalities, mixed gender and age. However the advantage is that the class is small.  The basic knowledge of the students are evaluated using algebraic and arithmetic quizzes conducted in the moodle. The results are immediately displayed after completion within a speculated time. Based on the assessment and personal tutoring sessions (provided to each individual), the major challenges faced during the lecture of this module are

·         A notion that mathematics is tough

·         Lack of interest to Mathematics and just get through it to become engineers

·         How students can grasp the understanding of ideas as a consequence of exploring problems situation

# data[].attributes.body
The module considered for the critical evaluation is of HE4, Mathematics and Structural Analysis (CIE4011). The module briefs fundamentals of Civil Engineering which is also a prerequisite of modules of HE5 and HE6.  Its purpose is to develop the students’ ability to solve problems using engineering mathematics and structural analysis techniques in order to create an inductive approach of learning

Therefore the main goal is to design instructions that facilitates learning which encourages autonomy and independent thinking of students (wordpress.com,2012)