This study aims to find and assess the literature on technology (Software, artificial intelligence, blockchain, cloud, big data, enterprise resource planning, information communication technology, data analytics, mobile computing, fintech, internet of things, and computer assisted auditing techniques) in accounting teaching and learning. A comprehensive analysis of the literature on the subject was conducted by the authors, who consider 66 papers that were found in the Scopus database. To analyze and outline potential areas for future research in this area, the authors also used a bibliometric analysis to pinpoint the key features of these studies. The study highlights technology usage in accounting teaching and learning and prominent research contributors. The study identifies recent technologies in accounting courses, such as ChatGPT, AI, gamified mobile learning, big data analysis, cloud computing, Linux-based teaching platforms, blockchain coding, storytelling methods, practical exercises, and software usage. It also suggests future avenues for higher educational institutions (HEIs) to integrate these technologies into accounting education. Further, the study suggests future avenues for HEIs to include the latest technologies in teaching and learning in accounting. The analysis draws attention to a few areas that were under-researched at the beginning of the research process in the area of technology teaching and learning in accounting, such as the growing use of fintech, crowdfunding, and computer assisted auditing techniques which are all used as new terms to improve accounting teaching and learning which can be suggested to incorporate into university curricula. The study provides valuable insights into enhancing higher education accounting teaching and learning systems, specifically by incorporating various technologies. These findings significantly contribute to the ongoing discussion on improving accounting teaching and learning. This study is the first to examine how technology enhances teaching and learning in accounting from an international perspective, which will aid researchers, academicians, and HEIs in understanding how the literature in this field of study is emerging. 

Surfing the technology wave: An international perspective on enhancing teaching and learning in accounting

Amidst the rapid advancement of digital technology, proficiency in Logical Thinking Skills and Digital Literacy stands pivotal for adapting to societal shifts, with Self-Learning Capability being fundamental for knowledge updating and skill acquisition to ensure success; however, despite their paramount significance for accounting students' success, research probing the intricate interplay among these three facets remains notably limited. Thus, this study examined the intricate interplay among Logical Thinking Skills, Digital Literacy, and Self-Learning Capability in shaping the effectiveness of accounting internships for Generation Z students in Thailand. Using a quantitative research design with online surveys, this study engaged 559 respondents (90.7 % females and 9.3 % males). Analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM), the study found that Logical Thinking Skills and Digital Literacy significantly influence internship performance. When complemented by Self-Learning Capability, it's observed that students with high competency in these areas can better apply their skills in real-world professional settings and demonstrate continuous learning. They actively incorporate online information and media into their learning and self-development, further enhancing their skill set and career proficiency. This study underscores the importance of accounting education in Thai educational institutions offering accounting programs. It emphasizes that these skills should be integrated into the curriculum, especially in the digital age, to equip students to adapt effectively to the evolving demands of the accounting profession. 

Impact of logical thinking skills and digital literacy on Thailand's generation Z accounting students’ internship effectiveness: Role of self-learning capability

Logos Verlag Berlin, Germany, Florian Berding, Julia Pargmann Iota Reliability Concept of the Second Generation. Measures for Content Analysis Done by Humans or Artificial Intelligences, Reihe: Berufs- und Wirtschaftspädagogik, Bd. 4 

Iota Reliability Concept of the Second Generation


Purpose
This study aims to extend the current literature on International Financial Reporting Standard (IFRS) teaching by examining the argument by Hodgdon et al. (2013) that arranging accounting prescriptions into the level of concept, principle and rules is helpful to students in comprehending the complex set of accounting standards. Besides, the study aims to attest the argument that analogy is a useful tool in teaching, especially when dealing with complex knowledge or concepts.


Design/methodology/approach
The study used a 3 × 2 between-subjects design, which includes the independent variables of the three-step teaching method (concept-only, concept + principle and concept + principle + rules) and the presence or absence of analogy.


Findings
The findings support Hodgdon et al. (2013). However, the combination of Hodgdon et al.’s (2013) technique with analogy resulted in only better-perceived comprehension under the concept-only condition.


Research limitations/implications
There are limitations to the use of analogy as an instructional tool. The reasoning behind an analogy is that it is produced from different fields in which the target and source topics have only some similarity in structure or function. This suggests a limited capacity in which the source topic can be used to fully explain a targeted topic, and thus caution needs to be exercised in the use of analogy as a teaching tool. Additionally, this study uses a perceived understanding of control in IFRS 15. While perceived understanding may likely result in actual comprehension, there is a possibility that this may not be the case. Finally, this study did not consider about how rule comprehensiveness is affected.


Practical implications
The findings of this study provide a useful combination of teaching tools to educators on how to deliver technical business subjects such as accounting effectively.


Originality/value
This paper aims to answer the call by Hodgdon et al. (2013) to verify the effectiveness of teaching IFRS via the three-step approach. In addition, this study extends the literature by examining whether an analogy could be used with the three-step approach to effectively improve students’ understanding of IFRS.


Teaching the concept of control under IFRS 15: the effect of a three-step teaching approach and analogy usage

Abstract This study explores the use of analytical artificial intelligence (AI) to enhance lesson planning in teacher education, particularly in vocational business education. Providing detailed, individualized feedback for lesson planning is challenging for university instructors. An analytical AI platform that offers expert-level feedback on lesson plans could be a suitable supplement to traditional feedback as it balances out critical aspects of generative AI systems. In a longitudinal study with 103 participants, an experimental group received AI feedback on the lesson plans they developed throughout a semester, while a control group received human feedback. Results indicate that AI feedback can match or surpass human feedback in some dimensions, improving planning aspects like certain content-related sustainability aspects, action orientation, relatedness or even technology use, lesson structure, and learner engagement. Besides the integration of didactic planning dimensions into the lesson plans, this study looked at student motivation, self-reported AI literacy, AI attitudes, self-efficacy with digital technologies and digital competences. Results of these meta-dimensions show that the mere use of AI does not automatically enhance AI literacy, change attitudes or improve motivation. The study suggests that as a consequence, analytical AI platforms can effectively supplement traditional feedback but should be used within a holistic framework. 

pdf/how-ai-feedback-supports-lesson-planning-in-vocational-32xp6wrqjweu.pdf

How AI feedback supports lesson planning in vocational teacher education: a longitudinal intervention study using an analytical AI platform

Learning analytics represent a promising approach for fostering personalized learning processes. Most applications of this technology currently do not use textual data for providing information on learning, or for deriving recommendations for further development. This paper presents the results of three studies aiming to make textual information usable. In the first study, the iota concept is introduced as a new content analysis measure to evaluate inter-coder reliability. The main advantage of this new concept is that it provides a reliability estimation for every single category, allowing deeper insight into the quality of textual analysis. The second study simulates the process of content analysis, comparing the new iota concept with well-established measures (e.g., Krippendorff’s Alpha, percentage agreement). The results show that the new concept covers the true reliability of a coding scheme, and is not affected by the number of coders or categories, the sample size, or the distribution of data. Furthermore, cut-off values are derived for judging the quality of the analysis. The third study employs the new concept, as it analyzes the performance of different artificial intelligence (AI) approaches for interpreting textual data based on 90 different constructs. The texts used here were either created by apprentices, students, and pupils, or were taken from vocational textbooks. The paper shows that AI can reliably interpret textual information for learning purposes, and also provides recommendations for optimal AI configuration.

Performance and Configuration of Artificial Intelligence in Educational Settings. Introducing a New Reliability Concept Based on Content Analysis

Abstract Tasks in accounting textbooks play a vital role when it comes to learning processes. However, hardly any empirical evidence on the quality of accounting tasks exists regarding accounting-relevant characteristics. This is why a new category system containing accounting-relevant aspects was developed to analyze a total of 3,361 tasks from 14 different German accounting textbooks. Descriptive analysis and correlation analysis were performed to assess task characteristics and identify relationships between categories. In addition, in light of the large number of tasks to be analyzed, AI assisted the content analysis, and its usefulness was evaluated. The results indicate that tasks are not sufficiently able to instill accounting competencies such as interpreting data, assessing the relevance of information, or identifying and solving underlying accounting problems. The findings further show that AI and human coding yield similar results in most categories, suggesting that AI assistance is useful for content analysis when evaluating a large number of tasks. 

/pdf/characteristics-of-learning-tasks-in-accounting-textbooks-an-127rj83y.pdf

Characteristics of learning tasks in accounting textbooks: an AI assisted analysis

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Performance and Configuration of Artificial Intelligence in Educational Settings. Introducing a New Reliability Concept Based on Content Analysis

Characteristics of learning tasks in accounting textbooks: an AI assisted analysis