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The Group of Twenty (G20) has substantial influence in global economic policy but has been peripheral in global education governance. There is intensification of education policy-relevant engagement within the Think 20 (T20), the “ideas bank” and official engagement group of the G20. The authors analyse the evolution of education as a policy domain within the T20, the ideas and discursive framing of education and global education policy “solutions” and assumptions about the G20 in education policy engagement.

The authors view the T20 as an external actor that can mobilise policy-relevant ideas to G20 actors responsible for internal policy selection and translation. The analysis covers the period 2018–2021 when education became an explicit T20 policy area. The authors screened all 461 T20 policy briefs across all domains. Of these, 32 briefs and four final T20 Summit communiqués were reviewed using critical discourse analysis. Data were supplemented via organisational websites and tacit professional knowledge.

Three assumptions on the G20 as an actor prevailed: (1) policymaker, (2) policy shaper and (3) knowledge mobiliser. The framing ideas on education were linked to assumptions on drivers of education system reform as intertwined with, or to enable: (1) economic adaptation, (2) technical adaptation and (3) socio-political adaptation of individuals and societies.

Accelerated education engagement within the T20 and its direct reach to G20 leaders makes it, and the G20, analytically unique and new unexamined actors of potential influence. The authors conclude that the T20 is positioned as a unique actor, both that can mobilise education policy-relevant ideas to G20 leaders, and legitimised as the actor from which G20 leaders and policymakers should adopt ideas.

Stakeholder theory understands business in terms of relationships among stakeholders whose interests are mainly joint but may be occasionally conflicting. In the latter case, managers may need to make trade-offs between these interests. The purpose of this paper is to explore the nature of managerial decision-making about these trade-offs.

This paper draws on the ordonomic approach which sees business life to be rife with social dilemmas and locates the role of stakeholders in harnessing or resolving these dilemmas through engagement in rule-finding and rule-setting processes.

The ordonomic approach suggests that stakeholder interests trade-offs ought to be neither ignored nor avoided, but rather embraced and welcomed as an opportunity for bringing to fruition the joint interest of stakeholders in playing a better game of business. Stakeholders are shown to bear responsibility for overcoming the perceived trade-offs through the institutional management of social dilemmas.

For many stakeholder theorists, the nature of managerial decision-making about trade-offs between conflicting stakeholder interests and the nature of trade-offs themselves have been a long-standing point of contention. The paper shows that trade-offs may be useful for the value creation process and explicitly discusses managerial strategies for dealing with them.

The authors constructed an automatic essay scoring (AES) model in a discussion forum where the result was compared with scores given by human evaluators. This research proposes essay scoring, which is conducted through two parameters, semantic and keyword similarities, using a SentenceTransformers pre-trained model that can construct the highest vector embedding. Combining these models is used to optimize the model with increasing accuracy.

The development of the model in the study is divided into seven stages: (1) data collection, (2) pre-processing data, (3) selected pre-trained SentenceTransformers model, (4) semantic similarity (sentence pair), (5) keyword similarity, (6) calculate final score and (7) evaluating model.

The multilingual paraphrase-multilingual-MiniLM-L12-v2 and distilbert-base-multilingual-cased-v1 models got the highest scores from comparisons of 11 pre-trained multilingual models of SentenceTransformers with Indonesian data (Dhini and Girsang, 2023). Both multilingual models were adopted in this study. A combination of two parameters is obtained by comparing the response of the keyword extraction responses with the rubric keywords. Based on the experimental results, proposing a combination can increase the evaluation results by 0.2.

This study uses discussion forum data from the general biology course in online learning at the open university for the 2020.2 and 2021.2 semesters. Forum discussion ratings are still manual. In this survey, the authors created a model that automatically calculates the value of discussion forums, which are essays based on the lecturer's answers moreover rubrics.