Developing Internet Agents: A Tutorial Using Visual Basic 6.0

An agent is someone or something authorized to “act on behalf of” another person. In professional sports, for example, an athlete’s agent may be authorized to negotiate the athlete’s contract, but may or may not be authorized to accept the terms of a contract. Similarly, an Internet agent acts on behalf of a person who wishes to conduct some activity utilizing the Internet. The capabilities and authority invested in such an agent are at the discretion of the person it represents. Typically Internet agents perform search and data collection activities. They may or may not have authority to negotiate or conduct purchase or sale transactions. Internet agents have varying levels of sophistication including lifespan, error detection and recovery, data validation, and embedded intelligence (Kauffman et al. 1999). A simple Internet agent, for example, may contact a single Web site (e.g., Amazon.com), extract a single fact (e.g., the price of a specified book) and report that fact to the user. A more sophisticated Internet agent may contact multiple Web sites (e.g., Amazon.com and BarnesAndNoble.com), track facts for several days or weeks (e.g., prices of a basket of books), record those facts for later analysis (e.g., in a database), and conduct transactions (e.g., purchase a subset of the basket of books when prices and availability meet given criteria). Today’s component-based, rapid application development environments allow individuals with very limited programming experience to build relatively sophisticated Internet agents without lengthy courses in Internet protocols or advanced programming techniques. Using development environments such as Visual Basic 6.0, simple but non-trivial Internet agents can be specified using a handful of components and a few dozen lines of code. The following sections present a single example illustrating the most rudimentary capabilities needed to create an Internet agent. This agent merely retrieves the raw HTML from a specified URL. A more complete tutorial, available at http://www.internet- technology.org/tutorials/agents/visualbasic/march includes examples of more sophisticated agents having more useful capabilities. These include following links, extracting and interpreting the data, and storing that data in a database for later analysis

A Little Help can Be A Bad Thing: Anchoring and Adjustment in Adaptive Query Reuse

The anchoring and adjustment heuristic has been shown to be a pervasive technique that people use in judgment, decision-making, and problem-solving tasks to reduce cognitive burden. However, reliance on the anchoring heuristic often leads to a systematic adjustment bias, in which people fail to make sufficient adjustments for a particular task. In a study involving 157 subjects from six universities, we examined the effect of this bias on SQL query formulation under varying levels of domain familiarity. Subjects were asked to formulate SQL queries to respond to six information requests in a familiar domain and six information requests in an unfamiliar domain. For some, subjects were also provided with sample queries that answered similar information requests. To adequately adjust a sample query, a subject needed to make both surface-structure modifications that required little cognitive effort and deep-structure modifications that required substantially more cognitive effort. We found that reuse can lead to poorer quality query results and greater overconfidence in the correctness of results. We also show that the strength of the adjustment bias depends on domain familiarity. This study demonstrates that anchoring and adjustment extends to an important area in information systems use that has not been previously studied. We also expand the notion of anchoring and adjustment to include the role of domain familiarity

Recruiting IT Professionals in Academia

The purpose of the proposed tutorial is to chart the course of a successful recruiting cycle. Case studies and interactive discussion will be used to illustrate each step in the process. In addition, the presenters will provide insight to participants regarding how to take best advantage of the AIS / ICIS Web-based Placement services. The tutorial is aimed at administrative faculty as well as teaching faculty who serve on recruitment committees

Toward a Social Ontology for Conceptual Modeling

Conceptual modeling is fundamental to information systems requirements engineering. Systems analysts and designers use the constructs and methods of a conceptual modeling formalism to represent, communicate, and validate the contents, capabilities, and constraints of an envisioned information system within its organizational context. The value of such a representation is measured by the degree to which it facilitates a shared understanding among all stakeholders of (1) the organizational information requirements and (2) the ability of the envisioned information system to meet them [Wand and Weber, 2002]. We propose using the social ontology developed by John Searle [1995, 2006, 2010] as the basis for conceptual modeling and present a meta-model based on that ontology

Developing and Teaching IS97.2: Personal Productivity with Information Technology

It is common for university students either to have introductory skills in the basic desktop software packages or to obtain these skills by self-study modules or short courses. What students lack is an understanding of how to use desktop packages effectively to improve their productivity. This is the missing link in the curriculum. This tutorial describes one solution: the IS\u2797.2 course on Personal Productivity with Information Technology. An appendix presents a sample lesson used with this course

Advances in Data Modeling Research

In this paper, we summarize the discussions of the panel on Advances in Data Modeling Research, held at the Americas Conference on Information Systems (AMCIS) in 2005. We focus on four primary areas where data modeling research offers rich opportunities: spatio-temporal semantics, genome research, ontological analysis and empirical evaluation of existing models. We highlight past work in each area and also discuss open questions, with a view to promoting future research in the overall data modeling area

Using Educational Data Mining to Identify and Analyze Student Learning Strategies

This paper explores student learning strategies in an introductory spreadsheets course. Student study habits were tracked at a level of detail not available in previous research. Detailed data were collected regarding reading, video watching, actions in practice assignments, references to assignment instructions, and actions in graded assignments. The analysis indicates that student strategies cluster into four primary learning groups. The study provides insight into how instructors can develop their courses and lectures in ways that better match the learning strategies of their students

AMCIS 2022 Awards Luncheon

This is a video recording and PDF document with the AMCIS 2022 Awards Ceremony

Justifying Breaking the Glass: How Accountability Can Deter Unauthorized Access

This research-in-progress study examines how accountability—the expectation that one will be required to answer for one’s actions, and justification—the requirement to give reasons for performing an action—can reduce instances of break-the-glass violations—can encourage compliance with data access policies. We examine whether justification can embolden users to break the glass in warranted situations, and deter users in inappropriate situations. We propose a series of lab experiments to test our hypotheses. We expect that our results will have implications for research on information security policy (ISP) compliance and practice