Search results

Is there a secret recipe for economic growth?

No, there is no recipe, but we can extrapolate some pieces of advice from Adam Smith.

An economy can leave behind its “dull” stagnant state and grow when its markets expand, when the productivity of its workers increases thanks to high compensations, which are seen as incentives to work harder and when lobbying and cronyism are kept at bay. Luck plays a role too, but these three ingredients are necessary, even if not sufficient, for an economy to grow and thus be “cheerful.”

These three aspects – expansion of market, liberal compensation of workers and lobbying – especially combined, have often been underestimated in Smith’s understanding of the possible sources of economic growth.

By reconsidering the concept of the historic environment, the aim of this study is to better understand how heritage is expressed by examining the networks within which the cultural performances of the historic environment take place. The goal is to move beyond a purely material expression and seek the expansion of the cultural dimension of the historic environment.

Conceptually, the historic environment is considered a valuable resource for heritage expression and exploration. The databases and records that house historic environment data are venerated and frequented entities for archeologists, but arguably less so for non-specialist users. In inventorying the historic environment, databases fulfill a major role in the planning process and asset management that is often considered to be more than just perfunctory. This paper approaches historic environment records (HERs) from an actor network perspective, particularizing the social foundation and relationships within the networks governing the historic environment and the environment's associated records.

The paper concludes that the performance of HERs from an actor-network perspective is a hegemonic process that is biased toward the supply and input to and from professional users. Furthermore, the paper provides a schematic for how many of the flaws in heritage transmission have come about.

The relevance here is largely belied by the fact that HERs as both public digital resources and as heritage networks were awaiting to be addressed in depth from a theoretical point of view.

Large classes pose challenges in managing different types of skills (e.g. maths, subject-specific knowledge, writing, confidence and communication), facilitating interactions, enabling active learning and providing timely feedback. This paper shares a design of a set of assessments for a large undergraduate economics course consisting of students from diverse cultural backgrounds. The benefits, challenges and learning experiences of students are analysed.

Students worked in groups to complete an assessment with several questions which would be useful as a revision for the individual assessment, the following week. Survey questionnaires with Likert-type questions and open-ended questions were used to analyse the learning and skill development that occurred because of the group work. Responses to the open-ended survey questions were coded and analysed by identifying the themes and categorising the various issues that emerged.

This assessment design developed group working skills, created opportunities to interact and enhanced learning. The analysis of the responses found that working with peers enabled the students to generate their own feedback, clear doubts and learn to solve problems. Effective communication, planning meetings and working around the diverse group members’ strengths and weaknesses are some graduate skills that are developed in this group assessment. The challenges were arranging meetings, finalising assessments, engagement of group members and unreliable technology. However, the students found ways to overcome these challenges.

This assessment design can be useful in higher education practice by introducing a mechanism for authentic collaborative practice. This paper adds to the literature on peer interactions and group work and enables effective learning at scale.